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Over the past few decades, instrumentation and techniques for total knee arthroplasty have evolved from conventional manual tools to a wide range of technologies, including calibrated guides for accurate bone cuts and alignment, smart tools, dynamic intraoperative sensors for soft tissue balancing, patient-specific guides, computer navigation, and robotics. This review is intended to provide an overview of the latest advancements in total knee arthroplasty technology, address potential challenges and solutions related to the application of these technologies, and explore their limitations. [ABSTRACT FROM AUTHOR]

Computer navigation and robotic assistance may reduce total hip arthroplasty (THA) dislocations by improving the accuracy and precision of component positioning. We investigated dislocation rates for THAs using conventional techniques, robotic assistance, and computer navigation, while controlling for surgical approach, dual mobility (DM) use, and fluoroscopic guidance. We reviewed 11,740 primary THAs performed between June 2016 and December 2022, including 5,873 conventional, 1,293 with robotic-arm assistance, and 4,574 with navigation. The approach was posterior in 6,580 (56.0%), anterior in 4,342 (37.0%), and lateral in 818 (7.0%). A DM was used in 10.4%. Fluoroscopy was used in 3,653 cases and only with the anterior approach. Multivariate analyses yielded odds ratios (OR) for dislocation and revision. Additional regression analyses for dislocation were performed for approach and DM. Raw dislocation rates were as follows: conventional 1.2%, robotic 0.4%, navigation 0.9%, anterior with fluoroscopy 0.4%, anterior without fluoroscopy 2.3%, posterior 1.3%, and lateral 0.5%. Upon multivariate analysis, use of robotics was found to be associated with significantly reduced dislocation risk compared to conventional (OR: 0.3), as did anterior (OR: 0.6) compared to posterior approach; navigation and lateral approach were not found to be associated with a significant reduction in risk. For the anterior approach, multivariate analysis demonstrated that fluoroscopy significantly reduced dislocation risk (OR: 0.1), while DM, robotics, and navigation were not significant. For the posterior approach, the dislocation risk was lower with robotics than with conventional (OR: 0.2); the use of navigation or DM did not demonstrate a significant reduction in risk. The use of robotics was associated with a reduction in dislocations for this cohort overall. Further, fluoroscopy in the anterior approach and robotic assistance in the posterior approach were both associated with decreased dislocation risk. The role of imageless computer navigation and DM implants requires further study. [ABSTRACT FROM AUTHOR]

Traditional robotic devices are often bulky and rigid, making it difficult for them to adapt to the soft and complex shapes of the human body. In stark contrast, soft robots, as a burgeoning class of robotic technology, showcase exceptional flexibility and adaptability, positioning them as compelling contenders for a diverse array of applications. High-performance electrically responsive artificial muscle materials (ERAMMs), as key driving components of soft robots, can achieve efficient motion and deformation, as well as more flexible and precise robot control, attracting widespread attention. This paper reviews the latest advancements in high-performance ERAMMs and their applications in the field of soft robot actuation, using ionic polymer-metal composites and dielectric elastomers as typical cases. Firstly, the definition, characteristics, and electro-driven working principles of high-performance ERAMMs are introduced. Then, the material design and synthesis, fabrication processes and optimization, as well as characterization and testing methods of the ERAMMs are summarized. Furthermore, various applications of two typical ERAMMs in the field of soft robot actuation are discussed in detail. Finally, the challenges and future directions in current research are analyzed and anticipated. This review paper aims to provide researchers with a reference for understanding the latest research progress in high-performance ERAMMs and to guide the development and application of soft robots. • Inspired by the good performance of natural muscles, extensive attention has been paid to the study of artificial muscles. Based on the structure and properties of artificial muscles, the research progress of high-performance artificial muscle materials is systematically reviewed, the working principle of the device-driven deformation is comprehensively analyzed, and the material design, preparation process and characterization methods are deeply analyzed. • The opportunities and challenges of high-performance artificial muscle materials, especially ionic polymer-metal composites and dielectric elastomers, are discussed, and their future research directions are proposed, laying the foundation for further innovative research on artificial muscle materials and their application development in the field of soft robot actuation. [Display omitted] [ABSTRACT FROM AUTHOR]

Minimally invasive surgery has emerged as a favorable alternative to conventional surgery for various cardiac conditions. This study aimed to compare the perioperative outcomes and follow-up results of the robotic approach versus the sternotomy approach for left atrial myxoma (LAM) resection. We retrospectively analyzed the perioperative outcomes and follow-up results of 94 patients who underwent left atrial myxoma resection using either the sternotomy approach (n = 64) or the robotic approach (n = 30) at our center between January 2017 and April 2023. Multiple linear regressions were employed to examine the actual impact of the surgical approach on perioperative outcomes while controlling for potential confounding factors. There were no in-hospital deaths or follow-up deaths in the robotic group. Univariate analyses revealed that robotic LAM resection had a longer cardiopulmonary bypass (CPB) time (99.93 ± 22.30 vs. 76.28 ± 24.92, P < 0.001), longer aortic clamping time (57.80 ± 20.27 vs. 47.89 ± 18.10, P = 0.019), reduced postoperative drainage (P < 0.001), shorter mechanical ventilation time (P = 0.005), shorter postoperative bed-stay time (P < 0.001), shorter postoperative hospitalization time (P = 0.040), and higher hospital costs (P = 0.001) compared to the sternotomy group. After adjusting for baseline characteristics in a multiple regression model, a longer CPB time (B = 28.328; CI, 18.609–38.047; P < 0.001), longer aortic clamping time (B = 11.856; CI, 4.069–19.644; P = 0.003), reduced postoperative drainage (B = −200.224; CI, −254.962– –145.486; P < 0.001), shorter mechanical ventilation time (B = −3.429; CI, −6.562– –0.295; P = 0.032), shorter postoperative bed-stay time (B = −2.230; CI, −3.267– –1.193; P < 0.001), shorter postoperative hospitalization time (B = −1.998; CI, −3.747– –0.250; P = 0.026), and higher hospital costs (B = 2096.866, P = 0.002) were found in the robotic group. Furthermore, the robotic group exhibited a faster return to exercise compared to the sternotomy group (Log-Rank χ2 = 34.527, P < 0.001). Both the robotic and sternotomy approaches are viable and safe options for LAM resection. However, despite the higher costs, longer CPB time, and longer aortic clamping time associated with robotic LAM resection, this technique was correlated with reduced postoperative drainage and faster postoperative recovery compared to the sternotomy technique. [ABSTRACT FROM AUTHOR]

This research presents a novel approach to robotic grasping by integrating an attention mechanism and advanced U-Net architectures, specifically UNet and UNet++, into the Generative Grasping Convolutional Neural Network (GG-CNN). The proposed method, Attention UNet++ GG-CNN, aims to improve the performance and accuracy of robotic grasping predictions significantly. The attention mechanism allows the model to focus on the most relevant features in the depth image, enhancing the quality of grasp predictions. The UNet and UNet++ structures, renowned for their efficiency in semantic segmentation tasks, are adapted to generate a pixel-wise grasp quality map, providing a one-to-one mapping from depth images. The UNet++ structure, with its nested and dense skip pathways, further improves the model's ability to capture and propagate low-level details to higher-level features. This approach overcomes the limitations of traditional deep learning grasping techniques by avoiding discrete sampling of grasp candidates and reducing computation times. Preliminary results indicate that the Attention UNet++ GG-CNN significantly improves the accuracy and performance of robotic grasping,with the Attention UNet++ GG-CNN achieving Intersection over Union (IoU) scores up to 95.86%, and average performance metrics across 25%, 50%, and 75% thresholds reaching as high as 88.29%, confirming its potential for more effective and reliable robotic manipulation in various settings, paving the way for more efficient and reliable robotic manipulation in dynamic environments. [ABSTRACT FROM AUTHOR]

A controller is proposed to guide a multi-articulated robot vehicle (MARV) moving backwards, following a certain path. The ability to avoid fixed and moving obstacles is included, using the null space-based control technique to manage the conflicting tasks of following a path and avoiding obstacles. Additionally, control gains are modulated, thus reducing the risk of jackknifing. These new approaches are the contributions of the article. Results of laboratory-scale experiments with a MARV pushing one and two trailers are presented and discussed, which validate the proposed controller. Simulation results are also presented considering a MARV with three trailers, showing that the proposed controller can be adopted for larger articulated chains and another experiment that shows that it is possible to avoid moving obstacles. • Control of a multi-articulated robotic vehicle to follow a path when moving backwards. • Evasive maneuvers to avoid static or dynamic obstacles in the desired path. • Dynamic compensation to reduce the position errors for the rear of the last trailer. • Null space-based control approach hierarchic execution of complimentary subtasks. • Controller gain modulation as a tool to reduce the possibility of jackknife. [ABSTRACT FROM AUTHOR]

In the realm of autonomous robotics, navigating differential drive mobile robots through unknown environments poses significant challenges due to their complex nonholonomic constraints. This issue is particularly acute in applications requiring precise trajectory tracking and effective obstacle avoidance without prior knowledge of the surroundings. Traditional navigation systems often struggle with these demands, leading to inefficiencies and potential safety risks. To address this problem, our studies propose an algorithm that integrates machine learning and control concepts, especially through the synergistic software of a Q-learning set of rules and a (PID) controller. This technique leverages the adaptability of Q-learning pathfinding and the precision of PID control for actual-time trajectory adjustment, aiming to beautify the robotics' navigation skills. Our comprehensive technique includes growing a country-area version that integrates Q-values with the dynamics of differential power robots, employing Bellman's equation for iterative coverage refinement. This version enables the robotics' capacity to dynamically adapt its navigation techniques in reaction to instant environmental feedback, thereby optimizing efficiency and protection in actual time. The effects of our full-size simulations exhibit a marked improvement in trajectory-tracking accuracy and impediment-avoidance competencies. These findings underscore the capability of combining machine learning algorithms with traditional methods to increase autonomous navigation technology in robotic systems. Our effects, derived from full-size simulations, suggest that the integration of Q-learning with PID controller markedly improves trajectory tracking accuracy, reduces tour times to targets, and complements the robotics' ability to navigate round barriers. This incorporated method demonstrates a tremendous advantage over conventional navigation systems, providing a sturdy way to the challenges of autonomous robot navigation in unpredictable environments. [ABSTRACT FROM AUTHOR]

Robotic-assisted total knee arthroplasty is increasingly used in revision total knee arthroplasty (rTKA), with imageless systems recently receiving Food and Drug Administration (FDA) approval. However, there remains a paucity of literature on the use of robotic assistance in revision total knee arthroplasty (TKA). This paper describes the imageless surgical technique for robotic revision TKA using a second-generation robotic system and details both intraoperative and 90-day outcomes. This was a retrospective review of 115 robotic revision TKAs from March 2021 to May 2023 at 3 tertiary academic centers. Patient demographics, perioperative surgical data, and 90-day outcomes were collected. Pain and Patient-Reported Outcomes Measurement Information System scores preoperatively and postoperatively were recorded. All-cause reoperations at the final follow-up were detailed. The mean patient age was 65 years (range, 43 to 88), and 58% were women. The mean follow-up time was 13 months (range, 3 to 51). The most common indications for rTKA were instability (n = 37, 32%) and aseptic loosening (n = 42, 37%). There were 83 rTKAs to a posterior-stabilized liner, 22 to a varus-valgus constrained liner, and 5 to a hinged construct. The median polyethylene size was 11 (interquartile range, 10 to 13), and 93% of patients had their joint line restored within 5 millimeters of the native contralateral knee. Within the 90-day postoperative window, there were 8 emergency department visits and 2 readmissions. At the final follow-up, there were 5 reoperations and 2 manipulations under anesthesia. There were 4 patients who required irrigation and debridement after superficial wound dehiscence, and one had an arthrotomy disruption after a fall. This review demonstrates favorable intraoperative and 90-day outcomes and suggests that imageless robotic surgery is a promising modality in rTKA. Further studies comparing the longitudinal outcomes after robotic and conventional rTKA are warranted. [ABSTRACT FROM AUTHOR]

This paper introduces a novel resource-efficient control structure for remote path-following control of autonomous vehicles based on a comprehensive combination of Kalman filtering, non-uniform dual-rate sampling, periodic event-triggered communication, and prediction-based and packet-based control techniques. An essential component of the control solution is a non-uniform dual-rate extended Kalman filter (NUDREKF), which includes an h-step ahead prediction stage. The prediction error of the NUDREKF is ensured to be exponentially mean-square bounded. The algorithmic implementation of the filter is straightforward and triggered by periodic event conditions. The main goal of the approach is to achieve efficient usage of resources in a wireless networked control system (WNCS), while maintaining satisfactory path-following behavior for the vehicle (a holonomic Mecanum-wheeled robot). The proposal is additionally capable of coping with typical drawbacks of WNCS such as time-varying delays, and packet dropouts and disorder. A Simscape Multibody simulation application reveals reductions of up to 93% in resource usage compared to a nominal time-triggered control solution. The simulation results are experimentally validated in the holonomic Mecanum-wheeled robotic platform. • A novel, comprehensive periodic event-triggered networked control solution is proposed. • High reduction of resource usage (of up to 93%) can be reached while maintaining acceptable control performance. • A non-uniform dual-rate extended Kalman filter (NUDREKF) is essential in the control structure. • Some conditions are provided such that the prediction error of the NUDREKF is exponentially mean square bounded. • Real path-following control tests for a holonomic Mecanum-wheeled robot validate the control solution. [ABSTRACT FROM AUTHOR]

This article aims to explore the integration of ChatGPT, an advanced conversational artificial intelligence model, in the field of dentistry. The review primarily consists of information related to the capabilities and functionalities of ChatGPT and how these abilities can aid dental professionals. This study includes data from research papers, case studies, and relevant literature on language models, as well as papers on dentistry, patient communication, dental education, and clinical decision-making. A systematic approach was used to select relevant studies and literature. The selection criteria focused on papers that specifically discussed the integration of language models, ChatGPT in particular, in dentistry and their applications. The study findings revealed that ChatGPT has significant potential to revolutionize dentistry by offering various applications and benefits. It can enhance patient engagement and understanding through personalized oral health information and guidance. In dental education, ChatGPT can provide interactive learning, case studies, and virtual patient simulations. ChatGPT can also assist researchers in analyzing dental literature, identifying patterns, and generating insights. Moreover, it supports dentists with evidence-based recommendations, treatment options, and diagnostic support. Integrating ChatGPT in dentistry can be highly beneficial, but it is crucial to address ethical considerations, accuracy, and privacy concerns. Responsible implementation and continuous improvement of its functionalities are necessary to ensure that patient care and outcomes are improved. [ABSTRACT FROM AUTHOR]

Copyright of Agora (0211-6642) is the property of Universidad de Santiago de Compostela, Servicio de Publicaciones and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The manipulation of compliant objects by robotic systems remains a challenging task, largely due to their variable shapes and the complex, high-dimensional nature of their interaction dynamics. Traditional robotic manipulation strategies struggle with the accurate modeling and control necessary to handle such materials, especially in the presence of visual occlusions that frequently occur in dynamic environments. Meanwhile, for most unstructured environments, robots are required to have autonomous interactions with their surroundings. To solve the shape manipulation of compliant objects in an unstructured environment, we begin by exploring the regression-based algorithm of representing the high-dimensional configuration space of deformable objects in a compressed form that enables efficient and effective manipulation. Simultaneously, we address the issue of visual occlusions by proposing the integration of an adversarial network, enabling guiding the shaping task even with partial observations of the object. Afterwards, we propose a receding-time estimator to coordinate the robot action with the computed shape features while satisfying various performance criteria. Finally, model predictive controller is utilized to compute the robot's shaping motions subject to safety constraints. Detailed experiments are presented to evaluate the proposed manipulation framework. Our MPC framework utilizes the compressed representation and occlusion-compensated information to predict the object's behavior, while the multi-objective optimizer ensures that the resulting control actions meet multiple performance criteria. Through rigorous experimental validation, our approach demonstrates superior manipulation capabilities in scenarios with visual obstructions, outperforming existing methods in terms of precision and operational reliability. The findings highlight the potential of our integrated approach to significantly enhance the manipulation of compliant objects in real-world robotic applications. • A parametric shape descriptor to efficiently characterize 3D deformations based on online curve/surface fitting. • A robust shape prediction network based on adversarial neural networks to compensate visual occlusions. • An optimization-based estimator to approximate the deformation Jacobian matrix and satisfy various performance constraints. • An MPC-based controller to guide the shaping motions while simultaneously solving saturation, workspace, and obstacle constraints. [ABSTRACT FROM AUTHOR]

Among the most well-known machine learning algorithms, Extreme Learning Machine (ELM) has seen widespread use across a variety of fields, including the defence and military industries. For problems like sluggish technique and iteratively altering the hidden layer's parameters to optimise the efficiency of the gradient descent approach, a cutting-edge machine learning algorithm known as the ELM has been developed. Depending on the specific objective and circumstance, the Extreme Learning Machine (ELM) may be more appropriate than Deep Neural Network (DNN) techniques. The models constructed in this manner perform quite well in generalisation. The following three goals are emphasised in its unconventional structure: 1) A great degree of accuracy in learning 2) less need for direct human involvement 3) an extremely rapid rate of learning, and moreover, it provides an optimal response for the whole world. As a result of its quick training, flexibility, and resilience, the Extreme Learning Machine (ELM) has several uses in this field, including target detection and tracking, image and signal processing, cybersecurity and intrusion detection, decision support systems, pattern recognition and classification, etc. According to our findings, the ELM approach was used with low training time and the testing accuracy is excellent. Also, this study presents the contribution of the revolutionary machine learning algorithm ELM to the defence and military sectors. [ABSTRACT FROM AUTHOR]

The coronal plane alignment of the knee (CPAK) classification system divides coronal knee anatomy into 9 phenotypes, suggesting different soft tissue balancing is needed for optimal outcomes. We investigated the interplay between CPAK phenotypes and gap stress curves throughout the knee's range of motion, aiming to understand their impact on total knee arthroplasty balancing. There were 1,112 total knee arthroplasty cases from 2 imageless robotic assisted navigation systems using posterior stabilized implants that were classified into CPAK phenotypes. Medial and lateral initial gap values were measured throughout the knee flexion-extension arc, gap curve morphologies were generated, and mediolateral (ML) gap balance was calculated for each phenotype. The most common phenotypes were included in this study, CPAK I to VI. Each phenotype exhibited a distinct gap curve morphology. Type I maintained the largest ML gap difference (−3.6 to −2.1), with the medial compartment tightest in extension. Type II showed relative laxity in the lateral compartment compared to the medial gap (−1.0 to −1.9), with the medial compartment tightening through flexion. Type III had a looser medial and tighter lateral compartment in extension that inverts to a tighter medial compartment in deep flexion (2.1 to −0.8), while Type IV showed a decreasing compartment difference with increased flexion (−3.7 to 0.6). Type V had fluctuating tightness (−0.6 to 1.8), and Type VI had the medial compartment tightening more with flexion (0.6 to 1.8). The distinct stress curves and ML gap behavior provide a "fingerprint" for each corresponding CPAK phenotype. Investigating these morphologies can help determine the best phenotype-specific treatments, including alignment strategy, implant selection, and gap balance, for optimal functional and patient outcomes. [ABSTRACT FROM AUTHOR]

While personalized, 3D printed, craniomaxillofacial (CMF) fixation plates are available from several vendors, given the short time window for reconstructive surgery in either advanced stage cancer resection or trauma, fixation plates are most often manually bent by eye. A surgeon's manual bending of fixation plates may significantly delay these time-sensitive procedures as well as introduce work hardening damage to the plate due to repetitive bending at one or more locations. Unfortunately, revision surgery can follow work hardening-induced fatigue failure, stress-shielding-induced bone loss, or stress concentration-induced fixation device failure. Our group has developed a desktop automated fixation plate bending unit for the robotic bending of CMF fixation plates. Our automated plate bending device consists of a pair of modular jaws that precisely hold a fixation plate and iteratively bend/twist it based on geometric data imported from a plate bending plan developed using 3D patient data and a VSP (Virtual Surgical Planning) environment. Our prototype plate bender offers accurate plate bending in a time frame that is much reduced versus traditional manual plate bending. The design details, and performance of this device are documented in this study. [ABSTRACT FROM AUTHOR]

Robotic-assisted Heller-Dor procedure has been proposed as an alternative minimally invasive approach to traditional laparoscopy for the treatment of achalasia in children. Our aim is to compare the effectiveness, safety and associated costs between both procedures. A retrospective single center study was conducted among consecutive children operated for achalasia (Heller–Dor operation) between 2005 and 2021, who were divided into two groups according to the surgical approach: laparoscopic (LAP-group) or robotic (ROB-group). Demographics, clinical features, surgery time, length of hospital stay (LOS), postoperative complications, long-term outcomes and economic data were compared between both groups. A total of 24 patients were included (12 in LAP-group; 12 in ROB-group), with no demographic or clinical differences between them. ROB-group patients presented lower intraoperative blood loss (23 ± 15 vs. 95 ± 15 ml; p < 0.001), shorter surgery time (178 ± 25 vs. 239 ± 55 min; p = 0.009) and shorter LOS, with a median of 2 days (Q1-Q3: 2–3) when compared to LAP-group (4 days [Q1-Q3:3-5]; p = 0.008). Three post-operative complications were reported, all in LAP-group (2 esophageal perforations and 1 esophageal tightness). After a median follow-up of 11 years, ROB-group patients presented fewer recurrences (0 vs 5; p = 0.039), less reintervention rate (0 % vs 41.7 %; p < 0.039) and lower associated economic costs (28,660$ vs. 60,360$; p < 0.001). This is the first comparative study of robotic and laparoscopic treatment of achalasia in children. Initial outcomes of robotic-assisted Heller-Dor procedure suggests some intraoperative (less blood loss and surgical time) and postoperative advantages (fewer complications and reinterventions). However, long-term studies with larger numbers of patients are needed. Retrospective comparative study. III. [ABSTRACT FROM AUTHOR]

Automated welding with robots is one of the core processes of modern manufacturing. Industrial robots are capable of continuously performing welding tasks under different working conditions in well-defined and structured environments. However, reprogramming in the plant is still necessary to deal with uncertainties due to a positioning error of the parts to be welded on the production line. This error can be due to several reasons, including dimensional quality of the parts, mechanical play, aging of the mechanisms, etc. In this sense, an automatic decision-making system is required to compensate for the measured error and avoid stopping the production line. In this work, we propose a controller based on the Enhanced Wagner-Hagras Interval Type-3 NSFLS-1 (EWH Type-3 NSFLS-1), a vision system and a laser beam incident on the plates to be welded to determine the misalignment that is corrected by a fuzzy controller. Type-3 fuzzy logic systems (T3 FLS) make it possible to model the effects of uncertainties and to minimize them by optimizing the parameters during the learning process of the fuzzy system. They can approximate any real continuous function on a compact set to arbitrary accuracy. In this article, several fuzzy logic algorithms were evaluated, resulting in the proposed EWH IT3 TSK NSFLS-1 controller being the best option since it presented the lowest error of 1.79e-09m to successfully reposition the robot. [ABSTRACT FROM AUTHOR]

• After stroke, effective rehabilitation technique is necessary for the affected limb. • Evidence regarding the role of RAT with ADL training for the impaired UL is lacking. • RAT and ADL training are more effective in UL motor recovery when compared with CRT. • RAT is a safe and effective approach in stroke rehabilitation. To evaluate the effectiveness of robot-assisted therapy (RAT) followed by activities of daily living (ADL) training in comparison with conventional rehabilitation therapy (CRT) and ADL training in individuals with subacute stroke. A single-blind, 2-arm, parallel-group, open-level, randomized controlled trial. A tertiary care teaching hospital in India. Forty-four persons (n=44) with first-ever stroke (in subacute stage) were enrolled from August 2021 to July 2023. Participants in the RAT group (n=22) received RAT for 30 minutes, followed by ADL training for 30 minutes. In contrast, participants in the CRT group (n=22) received CRT (30 minutes) followed by ADL training (30 minutes). Both groups received allocated interventions for 15 days over 3 weeks (5 days/week, 3 weeks). Primary outcome: Motor domain score of the Fugl-Meyer Assessment scale for upper extremity (FMA-UE). Secondary outcomes: the other domains scores of FMA-UE (UL -sensation, -joint motions, -joint pain); Modified Ashworth Scale (MAS) (spasticity); hand-function (HF) and ADL-domain scores of the stroke impact scale (SIS); WHOQQL-BREF questionnaires (QOL). Participants were assessed at enrolment and follow-up at 3, 6, and 12 weeks. Persons who received RAT and ADL training reported significant improvement (P <.05) in UL motor function (mean difference [MD]=3.54;(95% confidence interval [CI]: 1.28 to 5.79]), UL passive joint motions (MD=2.54; [95% CI: 1.56 to 3.52]), SIS-HF (MD=6.37;[95% CI: 4.75 to 7.99]), SIS-ADL (MD=7.13 [95% CI: 3.52 to 8.74]), and in all domains of WHOQOL-BREF (except environmental domain) compared with persons who received CRT and ADL training at 12 weeks. The findings indicate that RAT followed by ADL training is more effective than CRT followed by ADL training in motor improvement, SIS-HF, SIS-ADL, and QOL at 12 weeks. [ABSTRACT FROM AUTHOR]

This paper presents a two-loop control framework for robotic manipulator systems subject to state constraints and input saturation, which effectively integrates planning and control strategies. Namely, a stability controller is designed in the inner loop to address uncertainties and nonlinearities; an optimization-based generator is constructed in the outer loop to ensure that state and input constraints are obeyed while concurrently minimizing the convergence time. Furthermore, to dramatically the computational burden, the optimization-based generator in the outer loop is switched to a direct model-based generator when the tracking errors are sufficiently small. In this way, both a high tracking accuracy and fast dynamic response are obtained for constrained robotic manipulator systems with considerably lower computational burden. The superiority and effectiveness of the proposed structure are illustrated through comparative simulations and experiments. • A general and systematic constrained control scheme for robotic manipulators. • Nonlinearities, uncertainties, state and input constraints are considered. • Adaptive robust controller is designed for high tracking accuracy. • Optimization-based generator is designed for fast dynamic response. • Experiments on Franka robotic manipulator reveal the effectiveness. [ABSTRACT FROM AUTHOR]

Recently, the Internet of Things (IoT) technology has played a crucial role in our daily lives. It ensures the automatic transfer and response between various smart devices. Likewise, it enhances connections within networks and provides access to different information and data, making our lives easier. The innovation of the humanoid robot, which utilizes IoT technology, positively impacts our daily activities in many ways. However, compromising these robots may raise privacy and security concerns. This work aims to increase security awareness for robot users by highlighting and conducting common possible cyberattacks on Junior Zenbo robots using open, unsecured ports and weak Wi-Fi security, leading attackers to gain unauthorized access. In addition, the study intends to provide a comprehensive forensic guide that has been illustrated, detailing major Zenbo robot artifacts that can support forensic examiners in their investigations. [ABSTRACT FROM AUTHOR]

One of the most challenging robotic manipulator designs is finding an appropriate balance between the shaking force and shaking moment because this reduces vibrations. Several approaches have been introduced in the last decades; nevertheless, some assumptions must be established to make such a balance. In this paper, a dynamic balancing approach is proposed. The main novelty is the no dependence on specific trajectories to be executed by the manipulator, which allows finding a design with a similar tradeoff in the balancing under robot configuration changes. Also, the proposal incorporates mass distribution and link shape in a single design procedure. The proposal is stated as a constrained nonlinear optimization problem and applied to a hybrid serial-parallel robotic manipulator. The use of different bio-inspired algorithms and one gradient one in the solution of the balancing problem reveals that differential evolution finds the most suitable design. Besides, comparative simulation results of the obtained design with other design approaches show that the obtained design presents the most suitable tradeoff between the shaking force and the shaking moment when the manipulator executes tasks with different operating velocities. [ABSTRACT FROM AUTHOR]

Approximately 70% of chronic stroke patients experience upper extremity (UE) functional impairments, and UE outcome measures are often used as quality-of-life indicators. The purpose of this study was to estimate minimal clinically important difference (MCID) values for UE outcome measures in chronic stroke patients with moderate to severe UE hemiplegia. This study was a cross-sectional study, conducted as a secondary analysis of data from the ReoGo-J study, a multicenter, prospective, randomized, parallel-group trial of robot-assisted self-training for UE hemiplegia in chronic stroke. The patients were randomized to 1 of 3 treatment groups. Treatment was provided 3 times a week for 10 weeks, and UE outcome measures were evaluated before and after treatment. The anchor-based method was used to estimate MCID values for UE outcome measures, with Stroke Impact Scale (SIS) subscales as anchors. MCID values were estimated by identifying cutoff values in a receiver operating characteristic (ROC) curve. Between-group comparisons of UE outcome measures, based on the clinically important difference (CID) values of SIS subscales, revealed significant differences in both the Amount of Use (AOU) and Quality of Movement (QOM) components of the Motor Activity Log (MAL)-14. The estimated MCID values were 0.89 for the AOU component and 0.77 for the QOM component. The estimated MCID values for the MAL-14 not only add information regarding the clinical characteristics of the MAL-14 but also facilitate interpretations of changing scores in chronic stroke patients with moderate to severe UE hemiplegia undergoing rehabilitation therapy. (UMIN000022509; 1 July 2016). [ABSTRACT FROM AUTHOR]

Copyright of RED - Revista de Educación a Distancia is the property of Universidad de Murcia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a Distributed Discrete-time Exponential Sliding Mode Consensus (DDESMC) protocol is proposed for the leader-follower consensus of a Discrete Multi-Agent System (DMAS). The proposed protocol ensures not only the minimal consensus effort and reaching time for the consensus among the agents but also the minimum consensus deviation in the order of O (T 3). The consensus stability of DMAS with the proposed protocol is analyzed using Lyapunov theory and the maximum number of reaching steps required for achieving the consensus among all agents is calculated. The proposed protocol is validated in a simulation and experimental setup comprised of multiple 2-Degree of Freedom (DOF) robotic arms where one of the robotic arms is real, and others are virtual. Further, the consensus performance compared with the existing protocol in the literature, and it is inferred that the proposed protocol outperforms it in terms of time and effort required to achieve the consensus and the deviation from the consensus. • A novel DDESMC protocol to achieve the leader-follower consensus of a Discrete Multi-Agent System. • Minimal consensus effort and minimum reaching time to achieve the consensus. • Consensus deviation of the order O (T 3) after achieving the consensus. • Calculation for maximum number of steps required for achieving consensus. • Simulation and experimental validation with exhaustive performance comparison on a DMAS consist of multiple Robotic Arms. [ABSTRACT FROM AUTHOR]

Purpose: Partial nephrectomy is standard-of-care treatment for small renal masses. As utilization of partial nephrectomy increases and includes larger and complex tumors, the risk of conversion to radical nephrectomy likely increases. We evaluated incidence and reason for conversion to radical nephrectomy in patients scheduled for partial nephrectomy by surgeons participating in MUSIC (the Michigan Urologic Surgery Improvement Collaborative). Materials and Methods: All patients in whom robotic partial nephrectomy was planned were stratified by completed procedure (robotic partial nephrectomy vs radical nephrectomy). Preoperative and intraoperative records were reviewed for preoperative assessment of difficulty and reason for conversion. Patient, tumor, pathologic, and practice variables were compared between cohorts. Results: Of 650 patients scheduled for robotic partial nephrectomy, conversion to radical nephrectomy occurred in 27 (4.2%) patients. No conversions to open were reported. Preoperative documentation indicated a plan for possible conversion in 18 (67%) patients including partial with possible radical (n = 8), partial vs radical (n = 6), or likely radical nephrectomy (n = 4). Intraoperative documentation indicated that only 5 (19%) conversions were secondary to bleeding, with the remaining conversions due to tumor complexity and/or oncologic concerns. Patients undergoing conversion had larger (4.7 vs 2.8 cm, P < .001) and higher-complexity tumors (64% vs 6%, P < .001) with R.E.N.A.L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry score ≥ 10. The converted cases had a higher rate of ≥ pT3 (27% vs 8.4%, P = .008). Conclusions: There was a low rate of conversion from robotic partial to radical nephrectomy in the MUSIC-KIDNEY (Kidney mass: Identifying and Defining Necessary Evaluation and therapY) collaborative, and an even lower risk of conversion due to uncontrolled bleeding. Targeted review of each conversion identified appropriate decision-making based on oncologic risk in most cases. [ABSTRACT FROM AUTHOR]

The use of robotic platforms with social capabilities is becoming increasingly common to support people's daily lives. Such systems are commonly referred to as Socially Assistive Robots (SAR). Many SARs focus on a human-machine interaction based on visual and sound information, which could limit access for users with sight, hearing, or cognitive impairments, as it is usual in health environments. In this paper, we report a qualitative evaluation of the accessibility of Inrobics Rehab platform, arehabilitation platform based on the NAO robot. From the main outcomes, we propose to augment communication channels in social rehabilitation robots with haptic devices. The main aim of this proposal is to increase the accessibility of the platforms by combining multimodal information provided by visual, sound, and tactil channels. [ABSTRACT FROM AUTHOR]

The healthcare sector as a whole has a high administrative burden. Whether through doctors, nurses, laboratories, financial departments, accounting, pharmaceutical departments, among other entities, it is essential that everyone connects to monitor the patient. However, the administrative burden associated with these processes is extremely high which makes the tasks of the health sector more difficult to carry out. It is in this sense that the implementation of a technology such as Robotic Process Automation (RPA) allows all these routines but necessary tasks to be performed by capable software "robots" that respect rules that will allow to respond to all needs. It was found in the literature that there are few works related to the implementation of RPA in medical and healthcare services. The objective of this work is focused on a literature review to identify how RPA contributes to medical and health services in a context of sustainability. This work analyzes some studies available in the literature, analyzing them from the perspective of the Triple Bottom Line (TBL) related to environmental, social and economic effects. Regarding the results of this study, it appears that there is still a lot of room to improve research in this area, for example, with regard to the development of implementation models, governance and also to optimize the efficiency of RPA, in medical and healthcare administrative services, taking into account the TBL of the concept of sustainability. [ABSTRACT FROM AUTHOR]

This paper describes surface location error (SLE) for serial kinematic robot milling. It includes frequency-domain models for milling stability and SLE, which both use a mechanistic force model and tool tip frequency response functions as inputs. Based on the predictions, experimental conditions are selected and SLE experiments are completed for a selected geometry and 6061-T6 aluminum workpieces. Measurements and predictions are compared and the predictions are used to compensate the workpiece geometry and reduce SLE. It is observed that, due to the presence of both low stiffness, low frequency robot modes and high frequency tool-holder-spindle modes, the SLE is large, but nearly independent of spindle speed for the available range of spindle speeds. [ABSTRACT FROM AUTHOR]

Nowadays, research focusing on robotics, autonomous vehicles, and scene analysis shows a clear need for the ability to accurately reconstruct three-dimensional environments. One of the methods allowing to conduct such a reconstruction is to use a set of cameras and image processing techniques. This is a passive method. Despite being, in general, less accurate than its active counterparts, it offers significant advantages in numerous applications in which active systems cannot be deployed due to limited performance. This paper provides a theoretical analysis of the accuracy of estimating 3D positions of objects present at a given scene, based on images from a set of cameras. The analysis assumes a known geometrical configuration of the camera system. The important limiting factor in the considered scenario is the physical resolution of sensors-especially in the case of systems that are supposed to work in real time, with a high FPS rate, as the use of high-resolution cameras is difficult in such circumstances. In the paper, the influence of the geometric arrangement of the cameras is studied and important conclusions about the potential of three-camera configurations are drawn. The analysis performed and the formulas derived help predict the boundary accuracy values of any system using a digital camera. The results of an experiment that confirm the theoretical conclusions are presented as well. [ABSTRACT FROM AUTHOR]

The integration of Artificial Intelligence (AI) in pharmacy practice holds great potential to revolutionize healthcare delivery and improve patient outcomes. AI can assist pharmacists in optimizing medication selection, predicting adverse drug events and drug interactions, enhancing inventory management, and automating prescription verification. Moreover, AI-driven systems can facilitate personalized counseling and lifestyle management for patients, promoting treatment adherence and better health outcomes. However, the implementation of AI in pharmacy practice faces challenges, including ethical considerations, data privacy, and the need for comprehensive training for pharmacists. This review article explores how AI technology is revolutionizing medication management, pharmacist workflow, and patient care in pharmacy practice. Authors also explore the various applications and recommendations to overcome the barriers, providing valuable insights for pharmacists, healthcare professionals and policymakers.. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) has become a global health crisis in need of novel solutions. To this end, antibiotic combination therapies, which combine multiple antibiotics for treatment, have attracted significant attention as a potential approach for combating AMR. To facilitate advances in antibiotic combination therapies, most notably in investigating antibiotic interactions and identifying synergistic antibiotic combinations however, there remains a need for automated high-throughput platforms that can create and examine antibiotic combinations on-demand, at scale, and with minimal reagent consumption. To address these challenges, we have developed a Robotic-Printed Combinatorial Droplet (RoboDrop) platform by integrating a programmable droplet microfluidic device that generates antibiotic combinations in nanoliter droplets in automation, a robotic arm that arranges the droplets in an array, and a camera that images the array of thousands of droplets in parallel. We further implement a resazurin-based bacterial viability assay to accelerate our antibiotic combination testing. As a demonstration, we use RoboDrop to corroborate two pairs of antibiotics with known interactions and subsequently identify a new synergistic combination of cefsulodin, penicillin, and oxacillin against a model E. coli strain. We therefore envision RoboDrop becoming a useful tool to efficiently identify new synergistic antibiotic combinations toward combating AMR. We report the robotic-printed combinatorial droplet platform as a potential solution to automate and miniaturize the screening of antibiotic combinations to identify synergistic combinations for combating antimicrobial resistance. [Display omitted] [ABSTRACT FROM AUTHOR]

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Background/Purpose: Gait impairments in Parkinson disease (PD) contribute to decreased quality of life. This randomized controlled trial examined immediate- and longer-term effects of a single joint robotic exoskeleton device (EXOD), the Honda Walking Assist device, on gait. Methods: Participants (n = 45) with PD (Hoehn and Yahr stages 1-3) were randomized to a robotic-assisted gait training (RAGT) group (n = 23) or control (CON) group (n = 22). The RAGT group was tested with and without the EXOD at baseline and then received supervised in-home and community training with the EXOD twice weekly for 8 weeks. The CON group received no interventions. Outcome measures included gait speed (primary), gait endurance (6-minute walk test), perceived ease of walking, and questionnaires and logs assessing performance of daily activities, freezing of gait, and daily activity levels. Results: Forty participants completed the study. No significant immediate impact of EXOD usage on participants' gait measures was found. Differences in gait speed and secondary outcome measures postintervention were not significantly different between the RAGT and CON groups. Participants with greater disease severity (worse baseline motor scores) had greater improvements in stride length during unassisted walking after the intervention than those with lower severity (mean difference: 3.22, 95% confidence interval: 0.05-6.40; P = 0.04). Discussion and Conclusions: All RAGT participants could use the EXOD safely. The RAGT treatment used in this mostly low impairment population of people with PD may be ineffective and/or was insufficiently dosed to see a positive treatment effect. Our findings suggest that RAGT interventions in PD may be more effective in individuals with greater motor impairments. Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A459). [ABSTRACT FROM AUTHOR]

Robotics education has received widespread attention in K-12 education. Studies have pointed out that in robotics courses, learners face challenges in learning abstract content, such as constructing a robot with a good structure and writing programs to drive a robot to complete specific learning tasks. The present study proposed the embodied learning-based computer programming approach and applied it to the LEGO Mindstorms EV3 robotics course. To evaluate its effectiveness, a quasi-experiment was conducted in one public primary school to explore its effects on students' learning achievement, learning motivation, learning attitudes, learning engagement, and cognitive load. The experimental group (40 students) adopted the embodied learning-based computer programming approach, while the control group (40 students) adopted the conventional computer programming approach. The results showed that the experimental group had significantly better learning achievement in robotics than the control group, and that there was no significant difference in the cognitive load of the two groups. In terms of learning motivation, although both groups showed improvement, the experimental group had higher intrinsic learning motivation. In addition, the experimental group outperformed the control group with regard to learning attitudes and learning engagement (including cognitive, behavioral, and emotional engagement). Accordingly, this study could contribute to future research for developing more effective robotics teaching approaches and computer programming activity design. [ABSTRACT FROM AUTHOR]

Educational technologists and practitioners have made substantial strides in developing affordable digital and tangible resources to support both formal and informal computer science instruction. However, there is a lack of research on practice-based assignments, such as Internet of Things (IoT) projects, that allow undergraduate students to design and demonstrate educational robots using digital or physical assistance, especially when it comes to computational thinking (CT) and programming skills development in association with their psycho-emotional experience. This study compares the impact of Scratch and LEGO® WeDo robotic kits on students' CT and programming skills development. A quasi-experimental approach was conducted, involving two hundred forty-six participants (n = 246), who were equally divided between Scratch and LEGO® WeDo groups. Results indicate that the LEGO® WeDo group showed greater improvement in CT and programming skills development, while designing and presenting IoT projects. Nevertheless, no significant association between motivation, grit, and CT skills was observed. The findings highlight the potential of tangible robotics in facilitating students' hands-on learning and enhancing motivation to foster CT and programming skills. This study provides a wide range of implications for instructional designers on how to use tangible robotics to support hands-on IoT projects in computer science courses. [ABSTRACT FROM AUTHOR]

The subject's relevance stems from the rapid advancement of science and technology, which drives the extensive utilization of controlled mobile robot models with manipulators across diverse domains. The study aims to explore the development of versatile mobile robotic devices using manipulators for space applications, drawing from the expertise of specialists at Almaty University of Power Engineering and Telecommunications. The methodological approach is based on a combination of methods of system analysis of the principles of building a highly functional model of a mobile robot made based on manipulation devices, with an analytical study of the main directions of using mobile robots in the space sphere. The study underscores designing space mobile robots based on human body dynamics, stressing the necessity of robust mathematical models and specialized software, meeting stringent reliability, simplicity, and safety criteria. The findings underscored the critical role of manipulator-based mobile robot modeling in space technology development, offering practical insights for developers in various technological fields, including aerospace. The practical implications of the research include the possibility of developing and implementing reliable and efficient manipulative mobile robots for use in space, which will help to increase the efficiency of space operations and reduce risks to humans. [ABSTRACT FROM AUTHOR]

The development of advanced robotic systems that can be operated effortlessly by humans is crucial for expanding the capabilities of human-robot interaction and collaboration. In this work, we propose a system that enables real-time and non-invasive tracking of the human wrist's position in three-dimensional space to facilitate an intuitive control of a remotely placed robotic arm, as an improvement towards efficient control mechanism. We leverage color segmentation based human wrist tracking in the viewing plane augmented with a stereo depth estimation for synthesising the localized wrist in the Cartesian space. The centroid of the segmented image is determined to generate the precise coordinates. To remove the variance in the estimated centroid, the trajectory of the localized points is modelled by Kalman filtering approach. Finally, the coordinates are transformed using Inverse Imaging Model and transmitted to an edge device (close to the robot), which then replicates the motion at the robot end using inverse kinematics. The results show a high degree of accuracy in tracking the wrist's movements, enabling precise and natural control over the robotic arm's motion. The system's adaptability to various environments and user populations is validated through tests with diverse subjects. With its high accuracy, real-time performance, the proposed approach holds great potential to enhance the efficiency and safety of human-robot collaborative applications across multiple domains. [ABSTRACT FROM AUTHOR]

Benign prostatic hyperplasia (BPH) is a highly prevalent condition among aging men with significant negative impacts on quality of life. Although multiple surgical treatment modalities exist, there is an ongoing search for minimally invasive techniques to reduce hospital stays and adverse effects without compromising good functional outcomes. Aquablation is a novel minimally invasive surgical technique that combines robotic precision with heat-sparing ablation of obstructing prostate tissue. We describe the setup and mechanism of action of aquablation. A comprehensive literature search for clinical trials and recent meta-analyses was conducted and functional outcomes and adverse effects across multiple studies are summarized here. Aquablation produces comparable (if not superior) outcomes in terms of reduced International Prostate Symptom Score, improved Qmax (comparison of maximum flow velocity), and lower postvoid residuals to transurethral resection of the prostate. These findings are consistently reproduced across multiple clinical trials, including those conducted in the private sector. One major benefit of aquablation is that the risk of injury to the ejaculatory ducts appears to be significantly lower, as evident from the low percentage of cases of postoperative anejaculation issues. Adverse effects are rare, and the most significant one to mention is blood loss requiring transfusion. At present, the overall cost of aquablation is still higher than other methods of treating BPH and this is due to intraoperative and equipment costs. Postoperative care is no more expensive than other methods of BPH treatment. In conclusion, aquablation is a safe and effective surgical modality for the treatment of BPH. It can be offered as an alternative to other surgical modalities for those who wish to spare ejaculatory function. The procedure itself can be easily taught. With further development of this novel technology and increased availability, there is the potential for it to become a much more cost-effective method for surgical treatment of BPH. [ABSTRACT FROM AUTHOR]

Minimally invasive radical prostatectomy has become the standard surgical approach in the United Kingdom. Haematoma formation is a recognised post-operative complication, but this tends to be regarded as an early complication and there is a paucity of clinical information on the challenges of delayed haematoma formation. We present an unusual case of a man presenting with a late post-operative bleed that occurred spontaneously 5 weeks after surgery. A haematoma developed and was associated with complete disruption of the vesico-urethral anastomosis, that imaging had shown to be intact 11 days post-operatively. Level of evidence: 4 [ABSTRACT FROM AUTHOR]

Purpose: Numerous robot-assisted pancreatic surgery are being performed worldwide. This study aimed to evaluate the feasibility and safety of the Revo-i robot system (Meerecompany, Seoul, Republic of Korea) for advanced pancreatic surgery, and also compare this new system with the existing da Vinci™ robot system (Intuitive Surgical, Sunnyvale, CA, USA) in the context of robot-assisted pancreaticoduodenectomy (RPD). Materials and Methods: This study was a one-armed prospective clinical trial that assessed the Revo-i robot system for advanced pancreatic surgery. Ten patients aged 30 to 73 years were enrolled between December 2019 and August 2020. Postoperative outcomes were retrospectively compared with those of the da Vinci™ surgical system. From March 2017 to August 2020, a total of 47 patients who underwent RPD were analyzed retrospectively. Results: In the prospective clinical trial, pancreaticoduodenectomy was performed in nine patients and one patient underwent central pancreatectomy. Among the 10 study participants, the incidence of major complications was 0% in hospital stay. There were eight postoperative pancreatic fistula (POPF) biochemical leaks (80%). In the retrospective analysis that compared the Revo-i and da Vinci™ robotic systems, 10 patients underwent Revo-i RPD and 37 patients underwent da Vinci™ RPD, with no significant differences in complication or POPF incidence rates between the two groups (p=0.695, p=0.317). Conclusion: In this single-arm prospective study with short-term follow-up at a single institution, the Revo-i robotic surgical system was safe and effective for advanced pancreatic surgery. Revo-i RPD is comparable to the da Vinci™ RPD and is expected to have wide clinical application. [ABSTRACT FROM AUTHOR]

Teaching physical sciences presents a significant challenge in various countries, including Morocco, where student performance remains a subject of concern. This study aims to investigate the impact of introducing educational robotics as compared to computer-assisted experiments (EXAO) on students' motivation and learning in physical sciences. We divided a group of 120 middle-school students into two cohorts: one used the cost-effective educational robot, EducThermoBot, as an experimental group, while the other employed traditional EXAO as a control group. The findings demonstrate that the integration of educational robotics has a noteworthy and positive impact on students' motivation, whereas the overall academic performance exhibited no significant disparities between the two cohorts. Notwithstanding some limitations, this research offers valuable insights to enhance pedagogical practices by promoting the integration of educational robotics into the teaching of physical sciences in Morocco. [ABSTRACT FROM AUTHOR]

In this paper, a novel fuzzy adaptive sliding mode control method is proposed for realizing the asymptotic trajectory tracking of robotic manipulators with control backlash and uncertainties. The fuzzy logic system is introduced into the sliding mode control to estimate the system uncertainties. For compensating the unknown lumped disturbance and accelerating the convergence process, an adaptive super-twisting sliding mode controller is proposed with a novel adaptive law. The system states reach the sliding mode surface in a finite time and the control effect is continuous without over-estimation and control chattering. Depending on the Lyapunov stability theory, the tracking error converges to zero in a fast-exponential form. The effectiveness of the proposed method is fully indicated by the simulation of a robotic manipulator system. [ABSTRACT FROM AUTHOR]

This paper presents a control method for trajectory tracking of a robotic manipulator, subject to practical constraints and uncertainties. The proposed method is established upon an adaptive backstepping procedure incorporating a tangent-type barrier Lyapunov function and it preserves some important metrics of trajectory tracking such as fast and user-defined settling time response and robustness against actuation faults and unknown control gain. The proposed design maintains the system trajectory within a prescribed performance bound and relaxes the assumption of the bounded initial condition. These salient features preserve the system within a safety bound and, consequently, guarantee the system stability and safety. The performance of the proposed control method is validated on a 3-DOF PUMA 560 robotic manipulator benchmark model, with different operation scenarios. The simulation results confirm the effectiveness and robustness of the proposed control method. • This paper presents a prescribed trajectory tracking control of a robotic manipulator, subject to practical constraints. • The proposed design preserves user-defined settling time and unknown control gain. • The method maintains the system trajectory within a prescribed performance bound and relaxes the bounded initial condition. • A computationally efficient core function with an unknown scalar gain is used to enable real-time implementation in practice. • The performance of the method is validated on a 3-DOF PUMA 560 robotic manipulator benchmark model. [ABSTRACT FROM AUTHOR]

In this study, a three degrees of freedom (3 DOF) rigid-link robotic manipulator (RLM) has been simulated by using the Simscape model and the mathematical model derived by Lagrange method. The robot arm has been regulated by an Optimized PID Controller to achieve better tracking performance and reasonable robustness against disturbances and payload uncertainty. To optimize the controller, a novel nature-inspired Golden Jackal Optimization (GJO) algorithm has been used due to its efficient exploration that increases the diversity of the released solutions and its exploitation schemes which enhance the best-explored solutions. The tuning process has utilized a Lyapunov stability function as the objective function (OF) and the efficacy of the proposed algorithm is evaluated through a comprehensive comparison with various state-of-the-art metaheuristic techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Jellyfish Search Optimizer (JSO), Whale Optimization Algorithm (WOA), Arithmetic Optimization Algorithm (AOA) and Sine Cosine Algorithm (SCA). The assessment has been conducted on benchmark error-based functions, providing rigorous testing and validation of the algorithm's performance. Furthermore, the performance evaluation has focused on the system's robustness against disturbances, noise, and variations in the payload mass, particularly in the context of Pick and Place (PNP) industrial tasks. The results of simulation have demonstrated that the optimized system, employing the Lyapunov function, demonstrated superior performance in minimizing the objective function value compared to other benchmark functions. [Display omitted] • Efficient 3-DOF robotic model using MATLAB Simscape, enabling precise representation and efficient simulation. • Utilizing the new approach of Lyapunov function as the objective function in the optimization process. • Comparing the performance of the GJO algorithm with other recent optimization algorithms commonly used in the literature. • Comprehensive performance analysis to offer valuable insights into the controller's adaptability in real-world scenarios. [ABSTRACT FROM AUTHOR]

We propose a novel solution for generating robot tool paths to achieve uniform surface polishing of free-form poly-surfaces, addressing the limitations of imperfect surface reconstruction in real industrial settings and of abruptly varying curvatures. Existing approaches assume perfect 3D surface knowledge and overlook pieces with abrupt changes in principal curvatures, leading to unsatisfactory outcomes like non-smooth paths and incomplete coverage. Our research aims to develop an algorithm that adapts the polishing path for uniform coverage despite imperfect reconstruction or aggressive varying curvatures of the objects to be polished. Users can control the path points density, overlapping, edge proximity, and scanning direction. By segmenting the surface based on curvature similarity and connecting the separately computed trajectories, we minimize polishing time and achieve optimal polishing quality of free-form poly-surfaces in real industrial settings. [ABSTRACT FROM AUTHOR]

Moving from Industry 4.0 to Industry 5.0 marks a substantial shift in the way technology is incorporated into workplace design. In Industry 4.0, the emphasis was on automating the production process to maximize efficiency and output. However, with Industry 5.0, the focus has shifted towards placing people at the heart of the production process. This involves creating workspaces that prioritize human comfort and productivity and integrating technology that enhances human abilities. Collaborative robots, or cobots, are a critical technology in this transition as they work alongside humans to improve efficiency while enabling greater human involvement. However, to make the most of cobots, it is necessary to design workspaces that optimize human comfort and productivity, by considering the needs and preferences of both human and robotic resources. A promising strategy for achieving this goal is the implementation of a dynamic multi-objective task allocation system. The method proposed in this work uses physiological and performance data to assess the well-being of human operators and reallocates tasks dynamically to avoid overworking or fatiguing them. This represents a significant step towards creating production environments that prioritize the well-being and productivity of human workers. [ABSTRACT FROM AUTHOR]

The rapid advancement of robotics and artificial intelligence paves the way for collaborative robotics to revolutionise industrial operations. Collaborative robotics can bring significant improvements in productivity, efficiency, and safety. Recently, the concept of Symbiotic Human-Robot Collaboration (SHRC) has emerged within the field of collaborative robotics, emphasising the seamless and adaptive integration of human and robotic capabilities within a shared workspace to optimise overall production performance. However, existing collaborative systems frequently face difficulties in establishing dynamic relationships with humans and adapting to evolving conditions, ultimately restricting their overall potential. This paper investigates the essential features required for collaborative workstations to enable SHRC. Moreover, with the aim of fully harnessing the power of collaborative robotics, the paper introduces a design methodology that supports the development of symbiotic workstations for specific assembly operations. A real-world case study is provided, demonstrating the practical implementation and benefits of the proposed design approach. [ABSTRACT FROM AUTHOR]