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Advancements in bulk metallic glass thermoplastic forming unleash the potential to fabricate microscale metallic features with unparalleled precision and durability, i.e. microspine gripping structures for mobility platforms on planetary or in-space robots. Four designs of grippers were fabricated and rigorously tested. Coefficient of friction on four test surfaces were measured and compared to SiC paper and Velcro. The hardness and elasticity of the bulk metallic glasses make them a game-changer in the field, offering a superior alternative to conventional nonmetallic grippers. • Microspine grippers were manufactured via thermoplastic forming of bulk metallic glasses using silicon-on-insulator molds. • The microspines excelled on textured surfaces, where sharp points anchor on to pores or softer regions. • Mechanical behavior of microspines were studied using nanoindentor-based micro-compression and computer simulations. [ABSTRACT FROM AUTHOR]

Evidence shows stereotactic ablative body radiotherapy (SABR) is used as a non-invasive ablative therapy in the treatment of multisite oligometastatic (OM) and oligoprogressive (OP) diseases originating from metastatic breast cancer. This study aims to report the treatment outcomes and to investigate what factors that are prognostic in terms of local control, progression-free survival (PFS) and overall survival (OS) in patients receiving SABR for extracranial OM and OP diseases originating from metastatic breast cancer. A retrospective review on treatment records of patients with OM and OP from metastatic breast cancer who underwent SABR at a single was carried out. SABR was performed with daily image-guided radiotherapy (IGRT) using a dedicated robotic SABR machine. Local control, PFS and OS were calculated using Kaplan-Meier statistics and the post-treatment toxicity data was scored following the CTCAE v4.0 protocol. Univariate and multivariate Cox regression tests were used in the subgroup analysis of prognostic factors on PFS and OS including patients' age, types of follow-up imaging (staging CT only vs whole-body MR/PET), metastases status (OM vs OP), primary breast cancer tumour grade, hormone receptors (ER/PR/HER2) status, change of systemic treatments at SABR, number of metastases, SABR treatment sites and doses. 56 metastatic breast cancer patients (38 patients with OM and 18 patients with OP) were involved in this retrospective review. The median follow-up was 35.6 months (range 4.0–132.9 months). The estimated local control at 1 , 2 and 5 years were 90.9%, 88.7% and 88.7%, respectively. The estimated median PFS was 19.2 months (95%CI 10.3–28.1 months); the PFS at 1, 2 and 5 years were 63.3%, 44.4% and 33.2%. The estimated OS at 1, 2 and 5 years were 98.0%, 91.9% and 74.3%, respectively with the estimated median OS of 105.1 months (95%CI 51.5–158.7 months). The vast majority of patients tolerated the treatment well with the commonest acute side effects as grade 1 fatigue. There were no statistically significant factors found in OS regression analysis. The types of follow-up imaging, metastases status, oestrogen receptor status, and number of metastases for SABR were statistically significant factors (p < 0.05) in the multivariate Cox regression analysis on PFS. There are limited studies published on the efficacy and post-treatment toxicities of metastatic breast cancer OM and OP SABR with adequate length of follow-up. This study confirmed that SABR was a safe, non-invasive treatment option for patients with extracranial OM and OP diseases originated from primary breast cancer in terms of the acceptable post-treatment toxicities. • This study reported SABR treatment outcomes for multisite OM and OP diseases originating from metastatic breast cancer • It showed modest local control and post-treatment toxicities on the SABR of extracranial OM and OP from metastatic breast cancer. • The types of follow-up imaging, OM vs OP, oestrogen receptor status, and number of metastases for SABR can be used as PFS prognostic factors. [ABSTRACT FROM AUTHOR]

We Published a step–up approach for robotic training in hepato-pancreato-biliary (HPB) surgery has been previously. The approach was mostly based on personal experience and communications between experts and needed appraisal and validation by the HPB surgical community. At the Great Britain and Ireland HPB Association (GBIHPBA) robotic HPB meeting held in Coventry, UK in October 2022, the authors sought consensus from the live audience, with an open forum for answering key questions. The aim of this exercise was to appraise the step-up approach, and in turn, lay the foundation for a more substantial UK robotic HPB surgical curriculum. The study was conducted using VEVOX online polling platform at the October 2022 GBIHPBA robotic HPB meeting in Coventry, UK. The questionnaire was designed based on a literature search and was externally validated. The data were collated and analysed to assess patterns of response. A median (IQR) of 104 (96–117) responses were generated for each question. 93 consultants and 61 trainees were present Over 90% were in favour of a standardised training pathway. 93.6% were in favour of the proposed step-up approach, with a significant number (67.3%; p < 0.001) considering three levels of case complexity. The survey shows a favourable outlook on adopting step-up training in robotic HPB surgery. Ongoing monitoring of progress, clinical outcomes, and collaboration among surgeons and units will bolster this evidence, potentially leading to an official UK robotic HPB curriculum. [ABSTRACT FROM AUTHOR]

Videos on Robotic pancreaticoduodenectomy (RPD) may be watched by surgeons learning RPD. This study sought to appraise the educational quality of RPD videos on YouTube. One-hundred videos showing RPD or 'Robotic Whipple' were assessed using validated scales (LAP-VEGaS & Consensus Statement Score (CSS)). The association between the scores and the video characteristics (e.g. order of appearance, provider type etc) was assessed. The minimum number of videos required to cumulatively cover the entire LAP-VEGaS and CSS was also noted. The videos were of variable quality; median LAP-VEGaS = 0.67 (0.17−0.94), median CSS = 0.45 (0.29−0.53). There was no association between the educational quality of the videos and their order of appearance, view counts, provider type, length or country of origin. Videos lacked information such as patient consent (100%), potential pitfalls (97%) or surgeon credentials (84%). The first 29 videos cumulatively met all the criteria of CSS and LAP-VEGaS scores except for reporting consent. YouTube videos on RPD are of variable quality, without any recognised predictors of quality, and miss important safety information. An impractical number of videos need to be watched to cumulatively fulfil educational criteria. There is a need for high-quality, peer-reviewed videos that adhere to educational principles. [ABSTRACT FROM AUTHOR]

An efficient characterization of scientifically significant locations is essential prior to the return of humans to the Moon. The highest resolution imagery acquired from orbit of south-polar shadowed regions and other relevant locations remains, at best, an order of magnitude larger than the characteristic length of most of the robotic systems to be deployed. This hinders the planning and successful implementation of prospecting missions and poses a high risk for the traverse of robots and humans, diminishing the potential overall scientific and commercial return of any mission. We herein present the design of a lightweight, compact, autonomous, and reusable lunar reconnaissance drone capable of assisting other ground-based robotic assets, and eventually humans, in the characterization and high-resolution mapping (∼ 0.1 m/px) of particularly challenging and hard-to-access locations on the lunar surface. The proposed concept consists of two main subsystems: the drone and its service station. With a total combined wet mass of 100 kg, the system is capable of 11 flights without refueling the service station, enabling almost 9 km of accumulated flight distance. The deployment of such a system could significantly impact the efficiency of upcoming exploration missions, increasing the distance covered per day of exploration and significantly reducing the need for recurrent contacts with ground stations on Earth. • Sub-meter resolution data is required for an efficient lunar exploration. • Lightweight lunar aerobots can aid in the characterization of regions of interests. • Design is mostly based on space-proven, high-TRL, off-the-shelf components. • The presented design can map a range of 11 km with a total wet mass under 100 kg. [ABSTRACT FROM AUTHOR]

Monoclonal antibodies (mAbs) can be damaged during the aseptic compounding process, with aggregation being the most prevalent form of degradation. Protein aggregates represent one of several risk factors for undesired immunogenicity of mAbs, which can potentially lead to severe adverse drug reactions and less effective treatments. Since data on aggregate and particle formation by robotic compounding is missing, we aimed to compare the antibody stability between robotic- and manual compounding of mAbs with regard to formation of (sub)visible aggregates. Infliximab and trastuzumab were compounded into infusion bags with the APOTECAchemo robot or manually by nurses or pharmacy technicians. The products were analyzed by quantifying (sub)visible particles with nanoparticle tracking analysis, dynamic light scattering (DLS), light obscuration, micro-flow imaging, high pressure size exclusion chromatography (HP-SEC), and visual inspection. HP-SEC showed high percentages monomers in trastuzumab (99.4 % and 99.4 %) and infliximab (99.5 % and 99.6 %) infusion bags for both manual and robotic compounding, respectively. DLS indicated more consistent and reproducible results with robotic compounding, and confirmed monodisperse samples with a higher polydispersity index for manual compounding (0.16, interquartile range; IQR 0.14–0.18) compared to robotic compounding (0.12, IQR 0.11–0.15). This study shows that the studied compounding methods had a minor impact on the number of aggregates and particles, and that robotic compounding of mAbs provided at least similar quality as manual compounding. [ABSTRACT FROM AUTHOR]

With the ever increasing number of active satellites in space, the rising demand for larger formations of small satellites and the commercialization of the space industry (so-called New Space), the realization of manufacturing processes in orbit comes closer to reality. Reducing launch costs and risks, allowing for faster on-demand deployment of individually configured satellites as well as the prospect for possible on-orbit servicing for satellites makes the idea of realizing an in-orbit factory promising. In this paper, we present a novel approach to an in-orbit factory of small satellites covering a digital process twin, AI-based fault detection, and teleoperated robot-control, which are being researched as part of the "AI-enabled Cyber–Physical In-Orbit Factory" project. In addition to the integration of modern automation and Industry 4.0 production approaches, the question of how artificial intelligence (AI) and learning approaches can be used to make the production process more robust, fault-tolerant and autonomous is addressed. This lays the foundation for a later realization of satellite production in space in the form of an in-orbit factory. Central aspect is the development of a robotic AIT (Assembly, Integration and Testing) system where a small satellite could be assembled by a manipulator robot from modular subsystems. Approaches developed to improving this production process with AI include employing neural networks for optical and electrical fault detection of components. Force sensitive measuring and motion training helps to deal with uncertainties and tolerances during assembly. An AI-guided teleoperated control of the robot arm allows for human intervention while a Digital Process Twin represents process data and provides supervision during the whole production process. Approaches and results towards automated satellite production are presented in detail. • An automated production system for modular small satellites is proposed. • Central element is a force-sensitive robotic assembly, integration & testing system. • AI and machine learning approaches are applied to make the process more robust. • A digital process twin supervises the autonomous production. • A multi-modal shared control approach allows human teleoperation if required. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive survey of the integration of machine learning techniques into robotic grasping, with a special emphasis on the challenges and advancements for space applications. The incorporation of artificial intelligence, particularly through deep learning, reinforcement learning, transfer learning, convolutional neural networks and recurrent neural networks, has significantly revolutionized robotic grasping. These advancements facilitate autonomous, efficient, and sophisticated manipulation in the challenging environment of outer space, transitioning from traditional mechanical grippers to sophisticated systems powered by advanced algorithms. This transition highlights the critical integration of sensory perception, grasp planning, and execution mechanisms, enhancing robots' capabilities to perceive, interact with, and manipulate objects with unprecedented precision and adaptability. The article meticulously outlines significant advancements achieved through the deployment of convolutional neural networks for visual information processing, RNNs for sequential decision-making, RL for autonomous strategy refinement, and transfer learning for leveraging pre-learned knowledge in novel tasks. These technologies address the unique challenges of space environments, such as varied textures, occlusions, microgravity conditions, and the sim-to-real gap, by enhancing sample efficiency, improving sim-to-real transfer capabilities, and integrating multimodal data for better object localization and pose estimation. Furthermore, the review explores the specific challenges faced in space robotic grasping, including handling varied textures and occlusions, adapting to unpredictable conditions, achieving real-time processing, and ensuring safety and reliability. It proposes future research directions focused on overcoming these hurdles, such as enhanced generalization through multimodal learning, robust sim-to-real transfer techniques, and the development of collaborative robotics and swarm intelligence. Critical to the development of ML models for robotic grasping are the roles of specialized datasets and simulation environments. Datasets like the Cornell Grasping Dataset and the Yale-CMU-Berkeley Object, along with simulation platforms such as Gazebo and PyBullet, provide essential resources for training, testing, and refining ML models. These tools enable researchers to simulate complex robotic systems and interactions within realistic environments, fostering rapid iterations on design and control strategies. In summary, this article offers in-depth insights into the progress, current challenges, and future prospects of machine learning techniques in robotic grasping for space exploration. It showcases significant strides made in the field and charts a path forward, emphasizing the need for innovative solutions to navigate the complexities of robotic manipulation in outer space. Through the strategic integration of advanced ML techniques, the development of adaptable and efficient robotic systems for space applications continues to advance, promising to unlock new possibilities in space exploration and beyond. • Surveys machine learning's application in space robotic grasping, noting key advances. • Highlights CNNs and RNNs' roles in robotic perception and action. • Discusses deep learning's evolution in autonomous space robotics. • Outlines future directions, emphasizing sim-to-real and multimodal learning. [ABSTRACT FROM AUTHOR]

The 6-Degree-of-Freedom (6-DoF) robotic grasping is a fundamental task in robot manipulation, aimed at detecting graspable points and corresponding parameters in a 3D space, i.e affordance learning, and then a robot executes grasp actions with the detected affordances. Existing research works on affordance learning predominantly focus on learning local features directly for each grid in a voxel scene or each point in a point cloud scene, subsequently filtering the most promising candidate for execution. Contrarily, cognitive models of grasping highlight the significance of global descriptors, such as size, shape, and orientation, in grasping. These global descriptors indicate a grasp path closely tied to actions. Inspired by this, we propose a novel bio-inspired neural network that explicitly incorporates global feature encoding. In particular, our method utilizes a Truncated Signed Distance Function (TSDF) as input, and employs the recently proposed Transformer model to encode the global features of a scene directly. With the effective global representation, we then use deconvolution modules to decode multiple local features to generate graspable candidates. In addition, to integrate global and local features, we propose using a skip-connection module to merge lower-layer global features with higher-layer local features. Our approach, when tested on a recently proposed pile and packed grasping dataset for a decluttering task, surpassed state-of-the-art local feature learning methods by approximately 5% in terms of success and declutter rates. We also evaluated its running time and generalization ability, further demonstrating its superiority. We deployed our model on a Franka Panda robot arm, with real-world results aligning well with simulation data. This underscores our approach's effectiveness for generalization and real-world applications. [ABSTRACT FROM AUTHOR]

• Artificial intelligence in urology. • Artificial intelligence in robotic urological surgery. • Surgical intelligence identifying step annotations in urologic surgery. • Real-time artificial intelligence annotations in robotic surgery. Real-time artificial intelligence (AI) annotation of the surgical field has the potential to automatically extract information from surgical videos, helping to create a robust surgical atlas. This content can be used for surgical education and qualitative initiatives. We demonstrate the first use of AI in urologic robotic surgery to capture live surgical video and annotate key surgical steps and safety milestones in real-time. While AI models possess the capability to generate automated annotations based on a collection of video images, the real-time implementation of such technology in urological robotic surgery to aid surgeon and training staff it is still pending to be studied. We conducted an educational symposium, which broadcasted 2 live procedures, a robotic-assisted radical prostatectomy (RARP) and a robotic-assisted partial nephrectomy (RAPN). A surgical AI platform system (Theator, Palo Alto, CA) generated real-time annotations and identified operative safety milestones. This was achieved through trained algorithms, conventional video recognition, and novel Video Transfer Network technology which captures clips in full context, enabling automatic recognition and surgical mapping in real-time. Real-time AI annotations for procedure #1, RARP, are found in Table 1. The safety milestone annotations included the apical safety maneuver and deliberate views of structures such as the external iliac vessels and the obturator nerve. Real-time AI annotations for procedure #2, RAPN, are found in Table 1. Safety milestones included deliberate views of structures such as the gonadal vessels and the ureter. AI annotated surgical events included intraoperative ultrasound, temporary clip application and removal, hemostatic powder application, and notable hemorrhage. For the first time, surgical intelligence successfully showcased real-time AI annotations of 2 separate urologic robotic procedures during a live telecast. These annotations may provide the technological framework for send automatic notifications to clinical or operational stakeholders. This technology is a first step in real-time intraoperative decision support, leveraging big data to improve the quality of surgical care, potentially improve surgical outcomes, and support training and education. [ABSTRACT FROM AUTHOR]

This study evaluated the accuracy of the cup alignment angles and spatial cup positioning on computed tomography (CT) images in patients with osteoarthritis secondary to developmental dysplasia of the hip (DDH) who underwent total hip arthroplasty (THA) using a minimally invasive technique via an anterolateral approach in the supine position according to whether a robotic arm-assisted system or a CT-based navigation system was used. We reviewed 60 robotic arm-assisted (RA)-THA cases and 174 navigation-assisted (NA)-THA cases. After propensity score matching, there were 52 hips in each group. Postoperative cup alignment angles and position were assessed by superimposition of a three-dimensional cup template onto the actual implanted cup using postoperative CT images with pelvic coordinates matching the preoperative planning. The mean absolute error of the inclination angle and the anteversion angle between the preoperative planning and the postoperative measurement was significantly smaller in the RA-THA group (inclination, 1.1° ± 0.9; anteversion, 1.3° ± 1.0) than in the NA-THA group (inclination, 2.2° ± 1.5; anteversion, 3.3° ± 2.5). For acetabular cup positioning, the mean discrepancy between the preoperative planning and the postoperative measurement was 1.3 ± 1.3 mm on the transverse axis, 2.0 ± 2.0 mm on the longitudinal axis, and 1.3 ± 1.7 mm on the sagittal axis in the RA-THA group and 1.6 ± 1.4 mm, 2.6 ± 2.3 mm, and 1.8 ± 1.3 mm, respectively, in the NA-THA group. High precision of cup positioning was observed in both groups with no statistically significant difference. Robotic arm-assisted THA using a minimally invasive technique via an anterolateral approach in the supine position allows accurate cup placement in patients with DDH. [ABSTRACT FROM AUTHOR]

We report the world's first case series of ten robot-assisted radical prostatectomy (RARP) procedures performed with the Dexter robotic system (Distalmotion SA, Épalinges, Switzerland). The Dexter system is an open robotic platform that integrates into the existing operating room (OR) equipment. The optional sterile environment for the surgeon console provides flexibility for transition between a robot-assisted surgical procedure and a traditional laparoscopic setup, allowing surgeons to selectively use their preferred laparoscopic devices for specific surgical maneuvers on-demand. Ten patients underwent RARP ± lymph node dissection at Saintes Hospital (Saintes, France). Positioning and docking of the system were quickly mastered by the OR team. All procedures were successfully completed, without any intraprocedural complication, conversion to open surgery, or major technical failure. The median operative time was 230 min (interquartile range [IQR] 226–235), and the median length of stay was 3 d (IQR 3–4). This case series demonstrates the safety and feasibility of RARP with the Dexter system and provides the first insights into what an on-demand robotics platform could offer to hospitals willing to start or expand their robotic surgery program. [ABSTRACT FROM AUTHOR]

Object detection is one of the essential tasks in a variety of real-world applications such as autonomous driving and robotics. In a real-world scenario, unfortunately, there are numerous challenges such as illumination changes, adverse weather conditions, and geographical changes, to name a few. To tackle the problem, we propose a novel multi-modal object detection model that is built upon a hierarchical transformer and cross-guidance between different modalities. The proposed hierarchical transformer consists of domain-specific feature extraction networks where intermediate features are connected by the proposed Cross-Guided Attention Module (CGAM) to enrich their representational power. Specifically, in the CGAM, one domain is regarded as a guide and the other is assigned to a base. After that, the cross-modal attention from the guide to the base is applied to the base feature. The CGAM works bidirectionally in parallel by exchanging roles between modalities to refine multi-modal features simultaneously. Experimental results on FLIR-aligned, LLVIP, and KAIST multispectral pedestrian datasets demonstrate that the proposed method is superior to previous multi-modal detection algorithms quantitatively and qualitatively. [Display omitted] • Cross-guided attention mechanism by complementary interactions between modalities. • Multi-scale attention maps generated by the proposed hierarchical transformer. • State-of-the-art performance in FLIR-aligned, LLVIP, and KAIST multispectral datasets. [ABSTRACT FROM AUTHOR]

Active vision aims to equip computer vision methods with the ability to dynamically adjust the capturing sensor's viewpoint, position, or parameters in real time. This dynamic capability allows for improving the accuracy of the perception process. However, training and evaluating an active vision model often requires a large number of annotated images captured under different sensor and environmental settings, in order to emulate actions like moving around, approaching, or moving away from a person and thus effectively model the active perception dynamics. Obviously, collecting and annotating such datasets is a challenging and expensive task. To overcome these limitations, this paper introduces a synthetic image generation pipeline specifically designed to support active vision tasks. The pipeline is developed using a highly realistic simulation framework based on Unity and allows for the generation of images depicting humans, captured at varying view angles, distances, illumination conditions, and backgrounds, supporting a wide range of different tasks. Two annotated datasets, namely ActiveHuman and ActiveFace, are generated using the pipeline and the effectiveness of the proposed approach is demonstrated by a solid use case that involves training and evaluating an embedding-based active face recognizer. Furthermore, we demonstrate how the proposed generation approach enables expanding existing active face recognition methods by training models that control both the left/right movements, as well as the distance to a subject, leveraging the additional information provided by ActiveFace dataset. To facilitate replication and encourage the use of the generated datasets for training and evaluating other active vision approaches, the associated assets and the developed dataset generation pipeline is to become publicly available. • Active vision models require a large number of annotated data samples. • We propose a synthetic image generation pipeline designed to support active vision. • A highly realistic simulation framework based on Unity is used. • Two annotated datasets (ActiveHuman and ActiveFace) are generated. • Evaluation provided on a challenging active face recognition setup. [ABSTRACT FROM AUTHOR]

Robotic pancreaticoduodenectomy (RPD) is a safe and efficacious procedure in appropriately selected patients, though frequently with increased operative times compared to open pancreaticoduodenectomy (OPD). From 2014 to 2019, patients who underwent elective, low-risk, RPDs and OPDs in the NSQIP database were isolated. The operative time threshold (OTT) for safety in RPD patients was estimated by identifying the operative time at which complication rates for RPD patients exceeded the complication rate of the benchmark OPD control. Of 6270 patients identified, 939 (15%) underwent RPD and 5331 (85%) underwent OPD. The incidence of major morbidity or mortality for the OPD cohort was 35.1%. The OTT was identified as 7.7 h. Patients whose RPDs were above the OTT experienced a higher incidence of major morbidity (42.5% vs. 35.0%, p < 0.01) and 30-day mortality (2.7% vs. 1.2%, p = 0.03) than the OPD cohort. Preoperative obstructive jaundice (OR: 1.47, [95% CI: 1.08–2.01]) and pancreatic duct size <3 mm (OR: 2.44, [95% CI: 1.47–4.06]) and 3–6 mm (OR: 2.15, [95% CI: 1.31–3.52]) were risk factors for prolonged RPDs on multivariable regression. The operative time threshold for safety, identified at 7.7 h, should be used to improve patient selection for RPDs and as a competency-based quality benchmark. [ABSTRACT FROM AUTHOR]

To synthesise the evidence comparing the incidence rates of UAS post-RARC vs Open Radical cystectomy (ORC) in adults undergoing cystectomy and to compare differential stricture rates between Extracorporeal and Intracorporeal urinary diversion (ECUD vs ICUD). The primary outcome was incidence rate of UAS post RARC vs ORC and the secondary outcome was incidence rate of UAS in RARC post ECUD vs ICUD. Review authors conducted comprehensive search for studies comparing RARC with ORC in terms of incidence of UAS. Furthermore, we conducted a secondary search for studies which compared UAS incidence comparing ECUD and ICUD. We found that RARC may have higher incidence of UAS [OR: 1.39; 95% CI 1.11-1.75; p < 0.0001]. ECUD may result in lower rate of UAS as compared to ICUD [OR: 0.74; 95% CI 0.56 to 0.98; p= 0.04]. [ABSTRACT FROM AUTHOR]

The robotic arm has the characteristics of multi-degree-of-freedom motion and can perform complex tasks, making it the first choice to replace manual operations in space environment. However, traditional robotic arms still face many challenges in achieving both lightweight and high precision. To overcome this, we present an integrated stator-rotor piezoelectric actuator that integrates structural and functional design, enabling substantial weight reduction and high motion accuracy. The proposed design meets the requirements of the aerospace field, making it an ideal replacement for manual operations in space. The mechanism is composed of two sets of orthogonally linked rotary joints with driven arm joints enabling rotation in two vertical directions. To reduce the impact of clamping on vibration characteristics, the vibration modes and structural parameters are optimized through simulation. The size of the fabricated prototype is 160 × 60 × 60 mm, and its weight is only 24 g. The experimental results show that the maximum motion speed of the mechanism is 620 deg/s and the stalling torque is 20 mN m at 300 Vpp. The minimum resolution can reach 25 μrad in pulse mode, and a startup and shutdown response time of 45 ms and 31 ms at 200 Vpp, respectively. These characteristics verify the correctness of the design and show that the actuator has tremendous application potential. • The actuator has the characteristics of lightweight and high precision. • Using modal optimization to reduce the impact of clamping. • The rotary joint has the characteristics of structural and functional integration. • The proposed actuator has application potential in the field of precision drive. [ABSTRACT FROM AUTHOR]

Human desire to explore Mars has persisted throughout history, and especially, it is required to achieve precise and safe landings on the Martian surface. The atmospheric entry phase plays a crucial role in ensuring mission success, and active research on entry guidance methods continues. This paper presents a comparative study between the two primary types of entry guidance methods: (1) path planning-tracking and (2) predictor–corrector methods by applying them to solve two distinct Mars atmospheric entry guidance problems: (a) robotic entry and (b) human entry missions. Optimization approaches are adopted for the path planning-tracking method. After generating an optimal reference trajectory based on a mission concept-defined cost function, the receding horizon control method is employed to minimize tracking errors. In the predictor–corrector method, two parameterized entry guidance approaches are explored and analyzed. A well-known numerical predictor–corrector method that utilizes a parameterized bank angle profile for entry trajectory generation is tested to demonstrate its robustness against random dispersions. On the other hand, another predictor–corrector type guidance method that assumes a polynomial shape to shape an altitude profile over range-to-go is adopted to show its range control capability. Numerical simulations reveal the pros and cons of each type of entry guidance method, and a suitable guidance method for each Mars entry mission is identified depending on the mission concept and requirements. The analysis results provide future work. • A comparative study between path planning-tracking and predictor-corrector guidance methods. • Mars atmospheric entry problem for robotic and human landing missions. • Optimization approaches for reference trajectory generation and path tracking. • Numerical predictor-corrector based on parameterized bank angle and altitude profiles. [ABSTRACT FROM AUTHOR]

Stereoelectroencephalography (SEEG) remains critical in guiding epilepsy surgery. Robot-assisted techniques have shown promise in improving SEEG implantation outcomes but have not been directly compared. In this single-institution series, we compared ROSA and Stealth AutoGuide robots in pediatric SEEG implantation. We retrospectively reviewed 21 sequential pediatric SEEG implantations consisting of 6 ROSA and 15 AutoGuide procedures. We determined mean operative time, time per electrode, root mean square (RMS) registration error, and surgical complications. Three-dimensional radial distances were calculated between each electrode's measured entry and target points with respective errors from the planned trajectory line. Mean overall/per electrode operating time was 73.5/7.5 minutes for ROSA and 126.1/10.9 minutes for AutoGuide (P = 0.030 overall, P = 0.082 per electrode). Mean RMS registration error was 0.77 mm (0.55–0.93 mm) for ROSA and 0.6 mm (0.2–1.0 mm) for AutoGuide (P = 0.26). No procedures experienced complications. The mean radial (entry point error was 1.23 ± 0.11 mm for ROSA and 2.65 ± 0.12 mm for AutoGuide (P < 0.001), while the mean radial target point error was 1.86 ± 0.15 mm for ROSA and 3.25 ± 0.16 mm for AutoGuide (P < 0.001). Overall operative time was greater for AutoGuide procedures, although there was no statistically significant difference in time per electrode. Both systems are highly accurate with no significant RMS error difference. While the ROSA robot yielded significantly lower entry and target point errors, both robots are safe and reliable for deep electrode insertion in pediatric epilepsy. [ABSTRACT FROM AUTHOR]

Learning curve, training, and cost impede widespread implementation of new technology. Neurosurgical robotic technology introduces challenges to visuospatial reasoning and requires the acquisition of new fine motor skills. Studies detailing operative workflow, learning curve, and patient outcomes are needed to describe the utility and cost-effectiveness of new robotic technology. A retrospective analysis was performed of pediatric patients who underwent robotic stereoelectroencephalography (sEEG) with the Medtronic Stealth Autoguide. Workflow, total operative time, and time per electrode were evaluated alongside target accuracy assessed via error measurements and root sum square. Patient demographics and clinical outcomes related to sEEG were also assessed. Robot-assisted sEEG was performed in 12 pediatric patients. Comparison of cases over time demonstrated a mean operative time of 363.3 ± 109.5 minutes for the first 6 cases and 256.3 ± 59.1 minutes for the second 6 cases, with reduced operative time per electrode (P = 0.037). Mean entry point error, target point error, and depth point error were 1.82 ± 0.77 mm, 2.26 ± 0.71 mm, and 1.27 ± 0.53 mm, respectively, with mean root sum square of 3.23 ± 0.97 mm. Error measurements between magnetic resonance imaging and computed tomography angiography found computed tomography angiography to be more accurate with significant differences in mean entry point error (P = 0.043) and mean target point error (P = 0.035). The epileptogenic zone was identified in 11 patients, with therapeutic surgeries following in 9 patients, of whom 78% achieved an Engel class I. This study demonstrated institutional workflow evolution and learning curve for the Autoguide in pediatric sEEG, resulting in reduced operative times and increased accuracy over a small number of cases. The platform may seamlessly and quickly be incorporated into clinical practice, and the provided workflow can facilitate a smooth transition. [ABSTRACT FROM AUTHOR]

Vigorous research has been conducted to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics; however, these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Herein, we review developmental neurorobotic experiments tackling problems related to the dynamic and complex properties of neurodevelopmental disorders. Specifically, we focus on neurorobotic models under predictive processing lens for the study of developmental disorders. By constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neurodynamical, computational, and behavioral characteristics in the robot agents while considering developmental learning processes. This framework has the potential to bind neurobiological hypotheses (excitation-inhibition imbalance and functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotic approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

Robotic thoracic surgery is a minimally invasive technique that allows the surgeon to perform delicate, accurate surgical manoeuvres within the chest cavity without rib spreading. Previous studies have suggested potential benefits of the robotic platform in nodal upstaging due to its versatility, seven degrees of freedom of movement, and superior vision. However, there is currently a paucity of robust clinical data from Australia. This study aimed to assess the perioperative safety and oncological efficacy of anatomical pulmonary resections performed using the robotic platform. Endpoints included mortality and major morbidity outcomes according to Clavien–Dindo classification and rate of pathological nodal upstaging compared with preoperative imaging using positron emission tomography. A single-surgeon retrospective analysis was performed using data collected from two institutions from July 2021 to May 2022, after ethics committee approval. Consecutive patients who underwent anatomical robotic resections were included in the study, with subsequent analysis of patients who had confirmed primary lung cancer. A total of 52 patients underwent robotic anatomical pulmonary resection during the study period. Safety was demonstrated by 0% mortality and a 9.6% major complication rate, which was related to chest tube insertion for prolonged air leak or intensive care unit monitoring during treatment of atrial arrhythmia. After excluding patients who did not have primary lung cancer, 48 patients remained for further analysis; pathological nodal upstaging was observed in nine (18.8%) of these patients. On multivariate analysis, the total number of lymph nodes harvested was found to be a statistically significant predictor of nodal upstaging. Complete microscopic resection (R0) was achieved in 100% of patients. This study represents the most extensive documentation of robotic thoracic procedures in Australia in the existing literature. It demonstrated a satisfactory safety profile with a relatively high rate of nodal upstaging, possibly reflecting the ability of the robotic instruments to perform comprehensive and complete nodal resection at the time of anatomical pulmonary resection. [ABSTRACT FROM AUTHOR]

Cerebral palsy (CP) is a group of neuromotor diseases that develops as a result of damage to the developing central nervous system during the perinatal period. The condition is usually accompanied by musculoskeletal problems resulting in movement disorders. Gait improvement therefore, is an important part of its treatment. Roboticassisted gait training (RAGT) is a new potential rehabilitation tool for CP patients, however there is no clear evidence for the effectiveness of this method. Can robotic-assisted gait training improve walking function in children with CP? A systematic search was performed in five databases: MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Scopus, and Web of Science. Eligible studies were randomized controlled trials (RCT) with CP patients under the age of 18. Gross motor function and kinematic gait parameters of patients were the main outcomes. Two authors determined the risk of bias of the RCTs independently using the revised Risk of Bias 2 (ROB 2) tool. Mean Differences (MDs) along with their 95% Confidence Interval (CI) were calculated when at least three studies were present for an outcome, subgroup analysis was performed based on the treatment of the control group. Of the 7363 screened articles, 13 papers met our inclusion criteria and among them, 7 studies could be used in our meta-analyses. The results related to RAGT suggest nonsignificant improvement in standing and walking function (Gross Motor Function Measure D, E), moreover changes in gait speed, step length, and in cadence were also only comparable to controls. The results indicate that there is a trend in some gait parameters where the improvement was higher in the intervention group than in control group. The therapeutic effect of RAGT was probably not superior to physiotherapy combined with treadmill training. • Robotic-assisted gait training is a promising new treatment in cerebral palsy. • Effects and significance are not proven yet. • This review found a tendency for gait improvement after robotic training. • Straightforward evidence for effectiveness is still missing. [ABSTRACT FROM AUTHOR]

The development of autonomous robotic platforms for space applications such as satellites, robotic manipulators and rovers has driven the need for reliable control and navigation techniques. Simultaneous Localization and Mapping (SLAM) algorithms can be employed to determine the position and orientation of robotic platforms while generating a map of an unknown hostile environment. This article presents the successful integration of ORB-SLAM2, a localization algorithm, with Voxblox, an accurate three-dimensional mapping package. This integration aims to establish a pathway for occupancy maps to be generated from feature detection algorithms. Furthermore, virtual reality is presented as an innovative solution for testing the performance of this algorithm integration in a space environment. Providing a novel simulation environment with an opportunity to diversify applications. The effectiveness of this integration and SLAM accuracy was compared to a truth model extracted from the virtual reality environment. The accuracy is dependent on the number of observed and matched features in a given frame and are intrinsic characteristic of features in the environment. The robustness of the integration is also examined through the implementation of sensor inputs in the form of stereo and RGB-D cameras. The algorithms' integration and embedding into virtual reality allows for further developments of SLAM algorithms, to improve accuracy and robustness for autonomous navigation in any virtual environment, and extend robotic simulations and visualizations. [ABSTRACT FROM AUTHOR]

There is scant data on the role that robotics and navigation play in spine surgery training and practice of early attendings. This study aimed to assess the impact of navigation and robotics on spine surgery training and practice. A survey gathering information on utilization of navigation and robotics in training and practice was administered to trainees and early attendings. A total of 51 surveys were returned completed: 71% were attendings (average practice years: 2), 29% were trainees. During training, 22% were exposed to only fluoroscopy, 75% were exposed to navigation, 51% were exposed to robotics, and 40% were exposed to both navigation and robotics. In our sample, 87% and 61% of respondents who had exposure to navigation and robotics, respectively, felt that it had a positive impact on their training. In practice, 28% utilized only fluoroscopy, 69% utilized navigation, 30% utilized robotics, and 28% utilized both navigation and robotics. The top 3 reasons behind positive impact on training and practice were: 1) increased screw accuracy, 2) exposure to upcoming technology, and 3) less radiation exposure. The top 3 reasons behind negative impact were: 1) compromises training to independently place screws, 2) time and personnel requirements, and 3) concerns about availing it in practice. In sum, 76% of attendings felt that they will be utilizing more navigation and robotics in 5 years' time. Navigation and robotics have a perceivably positive impact on training and are increasingly being incorporated into practice. However, associated concerns demand spine surgeons to be thoughtful about how they integrate these technologies moving forward. [ABSTRACT FROM AUTHOR]

We assessed the feasibility of using compressed sensing accelerated, low-velocity encoded, isotropic resolution phase contrast (CLIP) magnetic resonance angiography (MRA) for avascular trajectory planning of stereoelectroencephalography. Ten healthy subjects (1 woman and 9 men; age, 33.6 ± 9.0 years) and 20 consecutive patients (12 female patients; age, 22 ± 13.6 years) were enrolled in the present study. The healthy subjects underwent CLIP-MRA, and 3 other phase contrast MRA protocols with conventional parallel imaging (PI) acceleration, including low resolution with twofold PI (PI2), high resolution (HR) with fivefold PI (PI5), and HR-PI2. The patients underwent CLIP-MRA and computed tomography angiography (CTA). The image qualities were evaluated. The numbers and locations of trajectory–vessel conflict detected using CLIP-MRA were noted. With similar scan durations, CLIP-MRA achieved higher spatial resolution compared with low resolution with PI2 and detected significantly more branches compared with HR-PI5. With the same spatial resolution, the signal/noise and contrast/noise ratios of CLIP-MRA were higher than those with HR-PI2 with a shorter scan duration. For the 12 adult patients (10 female patients; 28.8 ± 12.7 years), CLIP-MRA had better signal/noise and contrast/noise ratios than CTA. The trajectory had required modification for 14 of the 20 patients (70%), with a proportion of trajectory modification of 10.7% (23 of 215 electrodes). The middle meningeal artery, cortical vessel, and skull vessel were the main vessels with conflict (n = 11, n = 7, and n = 5, respectively). In the present study, CLIP-MRA provided a clear cortical vascular display noninvasively without intravascular contrast and radiation. The middle meningeal artery and diploic and emissary veins were the main conflict vessels and could be clearly displayed using CLIP-MRA but not CTA. [ABSTRACT FROM AUTHOR]

Minimally invasive approaches to the spine via anterior and posterior approaches have been increasing in popularity, culminating in the development of robot-assisted spinal fusions. The da Vinci surgical robot has been used for anterior lumbar interbody fusion (ALIF), with promising results. Similarly, multiple spinal robots have been developed to assist placement of posterior pedicle screws. However, no previous cases have reported on using robots for both anterior and posterior fixation in a single surgery. We present a technical note on the first reported case of a totally robotic minimally invasive anterior and posterior lumbar fusion and instrumentation. A 65-year-old man with chronic low back pain and left greater than right lower extremity radiculopathy was found to have grade 1 spondylolisthesis at L5/S1 that worsened on standing upright. He underwent ALIF using a da Vinci robotic approach, followed by percutaneous posterior instrumented fusion with the Globus Excelsius GPS robot. The patient did well postoperatively, with improvement of back and leg pain at 3 months follow-up. Radiography confirmed appropriate placement of the interbody cage and pedicle screws. All-robotic placement of both ALIF and posterior lumbar pedicle fixation may be safe, feasible, and efficacious. [ABSTRACT FROM AUTHOR]

In 2021 the Modular Mechatronics Infrastructure (MMI) was introduced as a solution to reduce weight, costs, and development time in robotic planetary missions. With standardized interfaces and multi-functional elements, this modular approach is planned to be used more often in sustainable exploration activities on the Moon and Mars. The German multi-robot research project "Autonomous Robotic Networks to Help Modern Societies (ARCHES)" has explored this concept with the use of various collaborative robotic assets which have their capabilities extended by the MMI. Different scientific payloads, engineering infrastructure modules, and specific purpose tools can be integrated to and manipulated by a robotic arm and a standardized electromechanical docking-interface. Throughout the MMI's design and implementation phase the performed preliminary tests confirmed that the different systems of the robotic cooperative team such as the Docking Interface System (DIS), the Power Management System (PMS), and the Data Communication System (DCS) functioned successfully. During the summer of 2022 a Demonstration Mission on Mount Etna (Sicily, Italy) was carried out as part of the ARCHES Project. This field scenario allowed the validation of the robotics systems in an analogue harsh environment and the confirmation of enhanced operations with the application of this modular method. Among the numerous activities performed in this volcanic terrain there are the efficient assembling of the Low Frequency Array (LOFAR) network, the energy-saving and reduced complexity of a detached Laser Induced Breakdown Spectroscopy (LIBS) module, and the uninterrupted powered operation between modules when switching between different power sources. The field data collected during this analogue campaign provided important outcomes for the modular robotics application. Modular and autonomous robots certainly benefit from their versatility, re-usability, less complex systems, reduced requirements for space qualification, and lower risks for the mission. These characteristics will ensure that long duration and complex robotic planetary endeavours are not as challenging as they used to be in the past. • Use of standardized interfaces and modular architectures in the field of robotics. • Modularity to extend the capabilities of robotic units. • Modular Mechatronics Infrastructure allows scientific tasks to be performed in a Moon Analogue environment. • Modularity in Robotics as solution for sustainable planetary exploration. [ABSTRACT FROM AUTHOR]

In order to establish the dynamic equations of the rigid-flexible coupled robotic mechanisms with large beam-deformations over the horizontal plane, a thorough modeling technique founded on the virtual work concept has been proposed. Based on the transformed full-actuated model, the predefined-time robust sliding mode control strategy is developed to track the prescribed angular positions of the rigid-flexible coupled robotic mechanisms. In addition to compensating the time-varying external disturbances, the nonlinear disturbance observer is also integrated and resolved into predefined-time robust sliding mode schemes. By introducing the virtual input, the robust linear quadratic state feedback controller is developed to eliminate the tracking errors and vibration modes of the rigid-flexible coupled robotic mechanisms simultaneously. Furthermore, it is proved that the tracking errors and vibration modes can be uniformly stable under the developed scheme based on Lyapunov's stability theory. Finally, three numerical examples are conducted to access the effectiveness and excellence of the presented nonlinear disturbance observer-based predefined-time robust sliding mode and robust linear quadratic state feedback strategies in comparison to nonlinear disturbance observer-based backstepping control and slide mode control schemes. [ABSTRACT FROM AUTHOR]

With the application of minimal invasive surgery during radical total gastrectomy, hand-sewing which is technology dependent is restricted. Materials and Methods Patients From December 2019 to August 2022, 30 patients underwent totally robotic radical total gastrectomy with the ALBS method for esophagojejunostomy by one experienced surgeon (Shuangyi Ren). Results A total of 30 patients underwent esophagojejunostomy using the ALBS method. [Extracted from the article]

• A generic non-linear post-capture detumble trajectory optimization formulation capable of including joint, base, and end-effector wrench limits. • A quaternion-based linearization of free-floating multibody system for trajectory tracking and stabilization. • A Lyapunov-based Region of Attraction analysis of the tracking controller. Recent increase in space debris combined with the increase in the number of satellites launched has created an increased risk of collisions. The effects of the increased risk can be seen in the form of an increased number of near misses in recent years. The use of robotic manipulators has been suggested for Active Debris Removal (ADR) to reduce the risk of potential future collisions that generate more debris in the orbits around Earth. Compared to other ADR methods, robotic manipulators provide increased versatility as they can be reused for On-Orbit Servicing as well as On-Orbit Assembly missions. A robotic ADR operation consists of three phases: Approach, Capture, and Detumble. This paper provides a method for performing feedback-based stabilization of post-capture detumble trajectories of the chaser-debris system. The approach presented here uses Time-Varying Linear Quadratic Regulator (TVLQR) for stabilization along the detumble trajectory. The contributions of this paper are as follows: A quaternion-based linearization method for multibody systems with a free-floating base, TVLQR for stabilizing the optimal detumble trajectory, and a probabilistic Region of Attraction analysis of the resulting closed-loop system. The estimated Region of Attraction could serve as the goal for the capture controller thus allowing for controller composition through ADR phases while guaranteeing stability and successful detumble. [ABSTRACT FROM AUTHOR]

This study reviews the current state of robotic surgery training for surgeons, including the various curricula, training methods, and tools available, as well as the challenges and limitations of these. The authors carried out a literature search across PubMed, MEDLINE, and Google Scholar using keywords related to 'robotic surgery', 'computer-assisted surgery', 'simulation', 'virtual reality', 'surgical training', and 'surgical education'. Full text analysis was performed on 112 articles. The training program for robotic surgery should focus on proficiency, deliberation, and distribution principles. The curricula can be broadly split up into pre-console and console-side training. Pre-Console and Console-Side Training: Simulation training is an important aspect of robotic surgery training to improve technical skill acquisition and reduce mental workload, which helps prepare trainees for live procedures. The study also discusses the various validated assessment tools used for operative performance assessments. Finally, the authors propose potential future directions for robotic surgery training, including the use of emerging technologies such as AI and machine learning for real-time feedback, remote mentoring, and augmented reality platforms like Proximie to reduce costs and overcome geographic limitations. Standardisation in trainee performance assessment is needed. Each of the robotic curricula and platforms has strengths and weaknesses. The ERUS Robotic Curriculum represents an evidence-based example of how to implement training from novice to expert. Remote mentoring and augmented reality platforms can overcome the challenges of high equipment costs and limited access to experts. Emerging technologies offer promising advancements for real-time feedback and immersive training environments, improving patient outcomes. • Progress in robotic surgery is democratising access. • Training programmes need expansion to produce safe, proficient robotic surgeons. • We review the current landscape of Robotic Surgery training. • We summarise future robotic surgery training practices. [ABSTRACT FROM AUTHOR]

Preoperative individual risk assessment together with appropriate imaging incorporating Ga-68 PSMA PET is very important in decision-making for the extent of the nerve sparing and keeping the margins tumor-free during a RARP. Neurosafe procedure led to more preserved keeping the margins tumor-free during a RARP. Neurosafe procedure led to more preserved and preoperative extracapsular extension suspicion in imaging together. Background: We aimed to analyze the effect of preoperative risk assessment including Ga-68 PSMA PET and multiparametric magnetic resonance imaging (mpMRI) on nerve sparing practices, positive surgical margin (PSM) rates and oncological outcomes based on a comparison between patients underwent RARP with and without Neurosafe (NS). Methods: Patients underwent RARP with NS (RARP-NS) or without (RARP-only) NS retrospectively evaluated. Suspicion for extracapsular extension on mpMRI and/or Ga-68 PSMA PET was recorded as i(imaging)T3. NS was performed according to the Martini-Klinik technique. PSM at preserved bundle side were called PSM at region of interest (ROI) while the others were elsewhere. Results: A total of 208 patients (90 in RARP-NS, 118 in RARP-only groups) were included. Preoperatively the RARP-only group showed significantly higher mean PSA (p = .01) and PIRADS 5 (p = .002) findings and had more D'Amico high risk (DAHR) patients (p = .08). The overall PSM rates for pT2 versus pT3 disease were 7.5% versus 21.6 and 15.6% versus 55% in RARP-NS and RARP-only groups, respectively. NS resulted in more bilaterally preserved bundles (81.1% vs. 66.3%) and less PSM at the ROI (3.3% vs. 23.4%) than RARP-only group. NS outperformed RARP-only in all clinical settings had its highest differential benefit in more bilateral nerve sparing and less PSM at ROI in patients with both DAHR and iT3 disease. BCR rates were 2.2% and 2.5% for RARP-NS and RARP only groups, respectively (p = .4). One patient in RARP-NS and 9 in RARP-only groups had PSA persistence (p = .02). Conclusion: RARP-NS led to more preserved bundles with less PSM. It was especially useful in DAHR patients with preoperative extracapsular extension suspicion in imaging simultaneously. [ABSTRACT FROM AUTHOR]

The 2022 incoming fellows' expectations for their robotics training, as well as their perceptions of the utility of the surgical robot, are not well defined. Cross-sectional survey of 24 AHPBA fellows in 2022, analyzed with descriptive statistics and Spearman's rho. Of 33 current AHPBA fellows, 22 completed the survey (66.7%). Study participants had limited-to-moderate experience with robotics prior to fellowship (mean 2.5 ± SD 1.1; range 1–4). Most participants agreed that robotics influenced their fellowship choice (mean 4.14 ± SD 0.87; range 1–5), would make then more marketable (mean 4.77 ± SD 0.52; range 1–5) and improve job prospects (mean 4.68 ± SD 0.87; range 1–5). Of the study participants, 55% responded that robotics training is "essential" in fellowship, while 64% responded that it is "essential" for their careers. Fellows were only slightly satisfied with overall robotics training within their respective programs (mean 3.44 ± SD 1.17; range 1–5) The majority (73.7%) expect that robotics will comprise <25% of their training. Notably, the majority (75%) have no formal robotics training curriculum. This survey identifies potential gaps where robotics training could be improved for future incoming AHPBA fellows. [ABSTRACT FROM AUTHOR]

To evaluate for differences in the perioperative and early postoperative outcomes between three different contemporary approaches of robotic radical prostatectomy (RARP), namely Single-Port (SP) Transvesical (TV), SP Extraperitoneal (EP), and Multi-Port (MP) Transperitoneal (TP). Retrospective review was performed on 865 consecutive patients with localized prostate cancer who underwent SP-TV, SP-EP, and MP-TP RARP. SP-TV and SP-EP RARP were performed using the purpose-built SP robotic platform. All procedures were performed by a single, experienced robotic surgeon. Demographics, perioperative, and early postoperative data were collected from the prospectively-maintained database. Statistical analysis was performed with descriptive statistics as presented. All SP cases were completed without any need for conversion or additional ports. When compared with MP-TP RARP, both SP-EP and SP-TV RARP were associated with significantly reduced length of stay (median, SP-TV 5.07 vs SP-EP 5.1 vs MP-TP 26.6 hours, P = <.05) and with most patients being discharged within 24 hours (SP-TV 92.3% vs SP-EP 84.6% vs MP-TP 30.4%, P = <.05). Postoperative analgesia requirements were significantly reduced following SP-TV RARP with 95% did not require opioid analgesia after discharge, as opposed to 77.6% and 12.1% of patients in the SP-EP and MP-TP RARP cohorts, respectively (P = <.05). Additionally, SP-TV RARP demonstrated the added benefit of a shorter Foley catheter duration of 4 days with an earlier return of urinary continence. The localization of RARP, as facilitated by the SP robotic platform, provided the opportunity for enhanced postoperative recovery resulting in decreased length of admission and postoperative pain, which allowed for increasing adoption of opioid-sparing outpatient prostatectomy. [ABSTRACT FROM AUTHOR]

• The physical-digital convergence of a programmable robot integrated into play has effects that enhance both spatial reasoning and computational thinking. • The teacher remained a key actor, providing verbal and nonverbal scaffolding to promote children's understanding and mastery of spatial and computational concepts. • Talking about spatial concepts combined with the interaction with a robot enhanced children's acquisition of spatial ideas. • The quantity of children's verbal expressions reflected the complexity of their applied spatial skills and computational thinking. Early evidence suggests that robot programming offers an important foundation for spatial reasoning and computational thinking; however, researchers have debated how to introduce young children to these skills. We explored how preschoolers develop understanding of spatial concepts and computational thinking as the children took turns navigating a path during guided play with a programmable robot. Our analysis of the data included a multimodal visualization of the exchanges between the teacher, children, and a programmable robotic device. The findings highlight the effects that arose from the physical-digital convergence of technology integrated into play including: (a) the robot evoked a chain of actions, enacting pedagogic forces that transformed children's learning; (b) children used their own bodies as spatial referents, co-locating themselves in space with the robot; (c) the teacher remained a key actor, providing verbal and nonverbal scaffolding to promote children's understanding and mastery of spatial and computational concepts; and (d) talking with the teacher about spatial concepts combined with the interactions with the robot enhanced children's acquisition of spatial ideas relative to the quantity of children's verbal expressions and complexity of their applied spatial skills and computational thinking. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive prescribed settling time periodic event-triggered control (APST-PETC) is investigated for uncertain robotic manipulators with state constraints. In order to economize network bandwidth occupancy and reduce computational burden, a periodic event-triggered control (PETC) strategy is proposed to reduce the update frequency of the control signal and avoid unnecessary continuous monitoring. Besides, considering that the maneuverable space of the actual robotic manipulators is often limited, the barrier Lyapunov function (BLF) is applied to deal with the influence of the constraint characteristics on the robotic manipulators. Further, based on the one-to-one nonlinear mapping function of the system tracking error, an adaptive prescribed settling time control (APSTC) is designed to ensure that the system tracking error reaches the predetermined precision residual set within the prescribed settling time. Finally, theoretical analysis and comparative experiments are given to verify its feasibility. • PETC is introduced to balance system bandwidth resources and monitoring requirements. • BLF is applied to handle the constraint characteristics on the robotic manipulators. • APSTC is proposed to ensure the system converges within the prescribed settling time. [ABSTRACT FROM AUTHOR]

The use of modular, yet reusable and interchangeable components offers flexibility for system designers and thus leads to a higher degree of reconfigurability with cost effective, adaptable and scalable solutions. The development of a robotic system remains, however, a complex task with increasing demands depending on the targeted capabilities, functionalities and operational constraints of the robot. This requires expert knowledge in mechanical, electrical and software engineering, as well as tools that can collect, process and use relevant data. As a result, the amount of available and managed information is increasing, while its relevance, usability, and knowledge that can be extracted from it are consequently decreasing: a situation described as information overload paradox. The design of a modular system can be based on the use of standardized modules with universal interconnects, but it should be aligned with a strong formalism, e. g. the semantic representation of components, to allow for a better management of the overall complexity. An ontology-based knowledge representation, for instance, which provides domain and application specific knowledge for the design of robotic systems, can be used as a method of storing and sharing data in a uniform, machine-readable and standardized way. In this paper, we introduce the Knowledge-based Open Robot voCabulary as Utility Toolkit (korcut) as a core component to support the ontology-driven development of robotic systems as part of a reference implementation of the Q-Rock development cycle. Q-Rock gathers methods to assist users in designing robot configuration by: (a) automatically exploring robot capabilities based on robot hardware, (b) proposing robot designs to meet the user's needs, (c) refining the proposed robot designs. We use korcut to improve the robot design process in orbital and planetary robotics from the requirements definition to the development phases of complex modular robotic structures (e. g. composition of an unmanned ground vehicle with robotic arms). This is implemented by embedding semantic component descriptions in a state-of-the-art open-source 3D modeling software. Furthermore, the korcut ontology family includes various sub-ontologies to address specific space-related tasks, such as the modeling of a Standard Interconnect (SI) for On Orbit Services (OOS) and Orbital Factory. The ontology design follows criteria that have been derived from a survey conducted as part of this work. This paper also covers an evaluation of its current applications from a methodological, knowledge representation, and software tool perspectives. In the application part, we introduce the use of the ontology to model a multi-functional SI that enables mechanical connections between various (modular) robotic components, as well as transfer of power and data. Finally, we provide a critical analysis of our work and outline its future work. • The development of complex robotic systems in space domain needs expert knowledge. • Increasing information about a robotic system can lead to an information paradox. • The information paradox can be improved by standardized and inferable knowledge. • Ontology is used in a case study to facilitate the robot development workflow. • Ontology is used to provide a metric for evaluating a space interface. [ABSTRACT FROM AUTHOR]

On-Orbit-Servicing missions aim to improve the operative life of orbiting satellites. Among the studied technologies, the most promising are satellites equipped with one or more robotic arms (space robots). One robotic arm might be employed to establish a rigid connection with the target satellite, while the other performs the servicing operations. Nowadays, the control of the capture tool is managed by the computer of the space robot. However, it is possible to distribute the control tasks between the capture tool and the space robot. For this purpose, this paper presents the development of the SMArt Capture Kit (SMACK). SMACK is a standalone capture system equipped with sensors, actuators, and an integrated computer. In this fashion, the capture tool executes the guidance and navigation algorithms, and the control of the actuators; so that the space robot acts as the "positioning" system for the capture tool. The paper provides a description of all the subsystems of SMACK and their experimental validation. The tests of SMACK at the system level, confirm its capabilities to autonomously perform the capture the target interface. • Smart capture tool. • Autonomous tool with integrated sensors, actuators and computer. • Distributed control. • Use of fuzzy logic to develop the model of a custom sensor. • Use of fuzzy logic to create the approach trajectory. [ABSTRACT FROM AUTHOR]

• Most agriculture robots and automated machines are still in development. • Occupational risks can and should be assessed of these emerging technologies. • NIOSH is working to better understand and mitigate these risks. Introduction : A variety of factors are driving the development of robotics and automation in the agriculture industry including the nature of work, workforce shortages, and a variety of economic, climatic, technologic, political, and social factors. While some new robotics and automated machines are available commercially, most are still being developed. This provides occupational safety and health researchers an unprecedented opportunity to mitigate risks and benefit the health and safety of agriculture workers. Method: The NIOSH Office of Agriculture Safety and Health (OASH) is working to better understand how the advancements in automation and robotics is affecting workers. OASH is coordinating with the NIOSH Center of Occupational Robotics Research (CORR) to help to increase the understanding of human/machine interactions; improve the ability to identify injuries and fatalities involving automation/ robotics; and provide guidance on working safely with automation/ robotics. OASH also joined a small team of academics and industry to organize the SAfety For Emerging Robotics and Autonomous aGriculture or (SAFER AG) Workshop to identify gaps in knowledge and research needs that connect to issues related to risks and regulations/standards, occupational safety research, and impacts on workforce and society. This workshop was sponsored by USDA NIFA. Practical Applications: Occupational safety and health experts need to engage and collaborate with developers of technology. It is also increasingly important for occupational safety and health researchers and practitioners to not only become familiar with existing manufacturing safety standards, but also the lengthy standards development process. Joining consensus standards groups to help shape new standards for emerging technologies may help to mitigate adverse worker impacts. NIOSH's Office of Agriculture Safety and Health will continue to identify research gaps, support new research projects, education, outreach efforts and the development of best practices with our partners. [ABSTRACT FROM AUTHOR]

Robotic neurosurgery is a rapidly advancing field with numerous applications in various subspecialties, including spine, functional, skull base, and cerebrovascular. This study aims to provide a comprehensive analysis of the most-cited articles on robotic neurosurgery. The Web of Science database was used to collect data, and bibliometric analysis was performed using VOSviewer and RStudio. Network analysis techniques such as co-occurrence, coauthorship, bibliographic coupling, and thematic mapping analyses were used to identify the top 100 most cited articles, major contributors, emerging trends, and noteworthy themes in the field. The results showed that there has been a steady increase in the number of publications on robotic neurosurgery since 1991, with an exponential growth in the number of citations. The United States was the most common country of origin for articles, followed by Canada. The most productive authors in this field were Burton S.A. and Gerszten P.C., while the University of Pittsburgh was the most productive institution, and Neurosurgery was the most productive journal. Themes such as robotics, back pain, and prostate cancer, as well as trends in developing new technologies and improving the precision of surgical procedures, were identified. This study provides a comprehensive analysis of the most-cited articles on robotic neurosurgery. The broad range of topics and techniques explored emphasize the importance of continued innovation and investigation. Ultimately, the study's findings provide valuable guidance for future research and contribute to advancing our understanding of this critical area of study. [ABSTRACT FROM AUTHOR]

The current success of Reinforcement Learning algorithms for its performance in complex environments has inspired many recent theoretical approaches to cognitive science. Artistic environments are studied within the cognitive science community as rich, natural, multi-sensory, multi-cultural environments. In this work, we propose the introduction of Reinforcement Learning for improving the control of artistic robot applications. Deep Q-learning Neural Networks (DQN) is one of the most successful algorithms for the implementation of Reinforcement Learning in robotics. DQN methods generate complex control policies for the execution of complex robot applications in a wide set of environments. Current art painting robot applications use simple control laws that limits the adaptability of the frameworks to a set of simple environments. In this work, the introduction of DQN within an art painting robot application is proposed. The goal is to study how the introduction of a complex control policy impacts the performance of a basic art painting robot application. The main expected contribution of this work is to serve as a first baseline for future works introducing DQN methods for complex art painting robot frameworks. Experiments consist of real world executions of human drawn sketches using the DQN generated policy and TEO, the humanoid robot. Results are compared in terms of similarity and obtained reward with respect to the reference inputs. • A Deep Q-Learning framework to draw human-like sketches using a humanoid robot. • Adaptability and scalibiliy of DQN introduced in an art painting robot application. • DQN Agent positions are translated to a real robot. • An additional DQN classification network improves the definition of the reward. • Baseline for future works introducing complex art painting robot applications. [ABSTRACT FROM AUTHOR]

The Institut Mutualiste Montsouris (IMM) classification system is one of several widely accepted difficulty scoring systems for laparoscopic liver resections. Nothing is yet known about the applicability of this system for robotic liver resections. We conducted a retrospective review of 359 patients undergoing robotic hepatectomies between 2016 and 2022. Resections were classified into low, intermediate, and high difficulty level. Data were analyzed utilizing ANOVA of repeated measures, 3 x 2 contingency tables, and area under the receiving operating characteristic (AUROC) curves. Data are presented as median (mean ± SD). Of the 359 patients, 117 were classified as low-difficulty level, 92 as intermediate, and 150 as high. The IMM system correlates well with tumor size (p = 0.002). The IMM system was a strong predictor of intraoperative outcomes including operative duration (p<0.001) and estimated blood loss (EBL) (p<0.001). The IMM system also showed a strong calibration for predicting an open conversion (AUC=0.705) and intraoperative complications (AUC=0.79). In contrast, the IMM system was a poor predictor of postoperative complications, mortality, and readmission. The IMM system provides a strong correlation with intraoperative, but not postoperative outcomes. A dedicated difficulty scoring system should be developed for robotic hepatectomy. [ABSTRACT FROM AUTHOR]