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Enabled via recent technological advances coupled with the advent of new systems providers and decreased price points, automated and robotized order-picking solutions (e.g., pick-assisting autonomous mobile robots) have evolved as a surging market. Such innovative picking technologies aim to reduce labor costs, use available space more efficiently, and increase throughput rates. As implementation projects and the variety of solutions rise, managers decide which ones to select for their specific warehouse and products. However, comprehensive decision models for this strategic problem are lacking in the pertinent literature. We propose a mathematical optimization model for the novel problem that selects and sizes order-picking solutions and assigns them products and warehouse spaces. Expert interviews are used to identify the comprehensive decision-relevant costs and constraints. Specifically, we minimize setup, module, labor, and error costs while adhering to characteristics related to the area (e.g., available space), technology (e.g., throughput, handling capabilities of certain products), and product (e.g., physical dimensions). We conduct a case study and complement our findings with numerical experiments. We find significant cost reduction potential of up to 57% by selecting a mix of different order-picking solutions. Further analyses highlight the need to retain human workers and to account for maximum labor capacity. [ABSTRACT FROM AUTHOR]

Advancements in automation technology have led to the increased utilization of industrial robots in manufacturing processes. Trajectory planning, which is crucial in robotics, involves designing smooth trajectories that adhere to constraints. Trajectory planning methods can be classified as either kinematic or dynamic, with dynamic models providing improved capacity utilization but requiring greater complexity. Given the need for efficient real-time implementation with low computational demands, the kinematic method is indispensable. The challenge lies in finding a balance between swift movements and minimal vibration, as smoother trajectories often necessitate higher-order polynomials, resulting in longer execution times and more intricate computations. Addressing the trade-off between speed and smoothness is crucial, as trajectory planning effectiveness depends on balancing energy efficiency, smooth motion, and computational complexity. A novel trajectory planner for point-to-point movements has been developed to enable rapid and smooth motion by integrating the advantages of minimum acceleration and minimum jerk trajectories. This innovative approach, tailored for a diverse range of robotic systems, generates a multi-objective and optimized trajectory as a single segment for seamless online implementation. Simulation and experimental tests were conducted to evaluate the proposed trajectory planner, comparing its performance against commonly used methods in terms of velocity, energy consumption, and smoothness.Article Highlights: An approach to trajectory planning for robotic systems is presented that effectively balances speed and smoothness. The proposed approach leverages the advantages of minimum acceleration and minimum-jerk trajectories. It facilitates online trajectory planning, allowing for boundary condition changes without computational complexity. [ABSTRACT FROM AUTHOR]

Background/Objectives: Robotic-assisted surgery has revolutionised modern medicine, enabling greater precision and control, particularly in microsurgical procedures. This systematic review evaluates the current state of robotic-assisted surgery across various specialties, focusing on four major robotic systems: Symani, Da Vinci, ZEUS, and MUSA. Methods: The review systematically analyses the effectiveness of these systems in performing vascular, lymphatic, and nervous anastomoses, comparing key metrics such as procedure time, success rates, and learning curves against manual techniques. It includes 48 studies, highlighting the technological capabilities and limitations of these systems in direct comparisons. Results: Results indicate that while robotic procedures often take longer than manual methods, significant improvements in efficiency are observed as surgeons gain experience. Conclusions: Overall, this study provides insights into the future potential of robotic-assisted surgery and highlights areas that require further research. It ultimately aims to promote the application of robotic systems in cranial neurosurgery, with a particular focus on advancing neurovascular techniques, such as microsuturing for bypass procedures. [ABSTRACT FROM AUTHOR]

Abstract Advancements in automation technology have led to the increased utilization of industrial robots in manufacturing processes. Trajectory planning, which is crucial in robotics, involves designing smooth trajectories that adhere to constraints. Trajectory planning methods can be classified as either kinematic or dynamic, with dynamic models providing improved capacity utilization but requiring greater complexity. Given the need for efficient real-time implementation with low computational demands, the kinematic method is indispensable. The challenge lies in finding a balance between swift movements and minimal vibration, as smoother trajectories often necessitate higher-order polynomials, resulting in longer execution times and more intricate computations. Addressing the trade-off between speed and smoothness is crucial, as trajectory planning effectiveness depends on balancing energy efficiency, smooth motion, and computational complexity. A novel trajectory planner for point-to-point movements has been developed to enable rapid and smooth motion by integrating the advantages of minimum acceleration and minimum jerk trajectories. This innovative approach, tailored for a diverse range of robotic systems, generates a multi-objective and optimized trajectory as a single segment for seamless online implementation. Simulation and experimental tests were conducted to evaluate the proposed trajectory planner, comparing its performance against commonly used methods in terms of velocity, energy consumption, and smoothness.

This paper describes a synthesis technique that constrains a spatial serial chain into a single degree-of-freedom mechanism using planar six-bar function generators. The synthesis process begins by specifying the target motion of a serial chain that is parameterized by time. The goal is to create a mechanism with a constant velocity rotary input that will achieve that motion. To do this we solve the inverse kinematics equations to find functions of each serial joint angle with respect to time. Since a constant velocity input is desired, time is proportional to the angle of the input link, and each serial joint angle can be expressed as functions of the input angle. This poses a separate function generator problem to control each joint of the serial chain. Function generators are linkages that coordinate their input and output angles. Each function is synthesized using a technique that finds 11 position Stephenson II linkages, which are then packaged onto the serial chain. Using pulleys and the scaling capabilities of function generating linkages, the final device can be packaged compactly. We describe this synthesis procedure through the design of a biomimetic device for reproducing a flapping wing motion.

The level of digitalization and automation, including robotic systems, is increasing in modern operating theaters. However, the integration of such systems within an already complex and limited environment creates challenges, such as collaboration with dynamic robots and thus potential collisions. Yet, the placements of robotic systems largely rely on empirical guidelines provided by manufacturers, which do not account for the specific requirements of operating theater layouts or individual surgical procedures. In this work, we propose a framework for optimization of robotic set-ups in the operating theater to address these limitations and to enhance the overall workflow efficiency. By utilizing a simulation-based approach, we aim to determine the optimal placement of each surgical equipment within the constrained operating theater environment. In this study, we set the stage for future efforts and demonstrate the effectiveness of our approach by determining the optimal placement of a LBR iiwa 7 R800 as a surgical assistant for an abdominal surgery. Overall this work lays the groundwork for future research that will accommodate more complex scenarios and is a crucial first step towards a holistic workflow optimization in the operating theater.

Introduction. The main issue in processing satellite measurements remains the struggle with their interference, especially intensive in rugged terrain, cities, atmospheric disturbances and artificial interference. Use of satellite navigation in recent years shows that such conditions undermine traditional satellite signal processing methods based on the least squares method or its modifications. These algorithms are unable to provide the required accuracy of spatial orientation for mobile robotic systems operating under intensive disturbances of various physical nature. This requires new algorithms for processing stochastic information more efficient than the least squares method, in particular, based on the theory of nonlinear stochastic filtration. The main challenge in this case is the synthesis of equations of motion of robotic complexes invariant to its type and random conditions of the environment of its functioning. At the same time, as practice shows, the vast majority of complexes move along programme trajectories that allow for analytical description of their motion parameters, which creates prerequisites for solving the problem of synthesis of these equations.Materials and methods. This paper proposes a navigation algorithm for robotic systems moving along a given trajectory under random perturbing factors. The algorithm is based on the combination of nonlinear stochastic filtering methods for estimating the state of dynamic systems operating under disturbances with non-traditional algorithms for processing satellite measurements and electronic map data.Results. For an environmental monitoring robot system, the authors modelled the motion in the plane of the local meridian from an initial point with longitude 30° and latitude 45°. The paper analyses the accuracy of the developed algorithm by estimating the trajectory of the robotic system using two classes of satellite navigation systems: medium and low precision.Discussion and conclusion. The results of the numerical experiment together with the above-mentioned advantages of the proposed method allow us to consider its effective practical application for positioning of mobile robotic systems.

Automating pruning tasks entails overcoming several challenges, encompassing not only robotic manipulation but also environment perception and detection. To achieve efficient pruning, robotic systems must accurately identify the correct cutting points. A possible method to define these points is to choose the cutting location based on the number of nodes present on the targeted cane. For this purpose, in grapevine pruning, it is required to correctly identify the nodes present on the primary canes of the grapevines. In this paper, a novel method of node detection in grapevines is proposed with four distinct state-of-the-art versions of the YOLO detection model: YOLOv7, YOLOv8, YOLOv9 and YOLOv10. These models were trained on a public dataset with images containing artificial backgrounds and afterwards validated on different cultivars of grapevines from two distinct Portuguese viticulture regions with cluttered backgrounds. This allowed us to evaluate the robustness of the algorithms on the detection of nodes in diverse environments, compare the performance of the YOLO models used, as well as create a publicly available dataset of grapevines obtained in Portuguese vineyards for node detection. Overall, all used models were capable of achieving correct node detection in images of grapevines from the three distinct datasets. Considering the trade-off between accuracy and inference speed, the YOLOv7 model demonstrated to be the most robust in detecting nodes in 2D images of grapevines, achieving F1-Score values between 70% and 86.5% with inference times of around 89 ms for an input size of 1280 × 1280 px. Considering these results, this work contributes with an efficient approach for real-time node detection for further implementation on an autonomous robotic pruning system. [ABSTRACT FROM AUTHOR]

In this paper, an event-triggered adaptive neural prescribed performance admittance control (ETANPPAC) scheme is proposed to control the constrained robotic systems without velocity sensors. To ensure compliance during human–robot interaction, the reference trajectory is obtained by reshaping the desired trajectory for the robotic systems based on the admittance relationship, where a saturation function is used to constrain the reference trajectory, avoiding excessive contact forces that could render the trajectory inexecutable. Moreover, a barrier Lyapunov function is used to constrain the tracking errors for prescribed performance, where a velocity observer and a radial basis function neural network are designed to estimate the velocity and the uncertainty of the robotic systems, respectively, to enhance control performance. To reduce the communication burden, an event-triggered mechanism is introduced and the Zeno behavior is avoided with the event-triggered condition. The stability of the whole control scheme is analyzed by the Lyapunov function. Simulation and experimental tests demonstrate that the proposed ETANPPAC scheme can track the desired trajectory well under constraints and reduce the communication burden, thereby achieving better efficiency for controlling the robotic systems compared with similar control schemes. • The ETANPPAC scheme achieves compliance and prescribed performance with constraints. • Barrier Lyapunov function constrains tracking errors, achieving desired performance. • Event-triggered method reduces the system burden and the Zeno behavior is avoided. • The proposed ETANPPAC scheme is tested on a numerical model and actual manipulator. [ABSTRACT FROM AUTHOR]

This paper aims to provide a global snapshot of concrete 3D-printed buildings and to uncover robotic-oriented large-scale fabrication strategies. Therefore, an extensive internet search and literature review was carried out to investigate 3D-printed buildings. In this study, 154 construction projects with 204 buildings were systematically recorded and evaluated from 2013 up to 2023. Using an exploratory mixed-methods approach and a comparative case study analysis, a total of 88 3D-printed buildings were first evaluated descriptively. Thereafter, different existing printing strategies for in situ, on-site, and off-site production were identified, using an iterative approach. In addition to the geographical distribution, the descriptive evaluation also showed the key players as drivers for the spread of the 3D-printing technology and the correlations between printer type, fabrication strategy, and the building size. With regard to the printing strategy, three different approaches for in situ and off-site fabrication can be defined, depending on the printer types and their characteristics (work size and mobility): print-in-one-go, horizontal or vertical segmentation, and the multi-element vs. full-scaled wall strategy. However, the study showed that the data quality was sometimes difficult due to a lack of information and essential details of the printing process and segmentation. [ABSTRACT FROM AUTHOR]

In the recent years, the use of artificial intelligence in the education domain has experienced a significant growth. The main reasons for this are the numerous innovative solutions, products and services, which are used not only in the educational processes, but also in the corresponding to them administrative activities. Based on this, the present publication aims to present the latest trends and the applications of the artificial intelligence in the education sector. This research has led to the identification of several key areas, in which the artificial intelligence has a significant contribution to the educational processes, including the adaptive assessment, the intelligent tutoring systems, the educational data mining, the personalized learning, the virtual reality, etc. This publication also presents some of the potential benefits, challenges and ethical considerations, which are associated with the use of the artificial intelligence technologies in the education. [ABSTRACT FROM AUTHOR]

Abstract Physical assistive robotics are oriented to support and improve functional capacities of people. In physical rehabilitation, robots are indeed useful for functional recovery of affected limb. However, there are still open questions related to technological aspects. This work presents a systematic review of upper limb rehabilitation robotics in order to analyze and establish technological challenges and future directions in this area. A bibliometric analysis was performed for the systematic literature review. Literature from the last six years, conducted between August 2020 and May 2021, was reviewed. The methodology for the literature search and a bibliometric analysis of the metadata are presented. After a preliminary search resulted in 820 articles, a total of 66 articles were included. A concurrency network and bibliographic analysis were provided. And an analysis of occurrences, taxonomy, and rehabilitation robotics reported in the literature is presented. This review aims to provide to the scientific community an overview of the state of the art in assistive robotics for upper limb physical rehabilitation. The literature analysis allows access to a gap of unexplored options to define the technological prospects applied to upper limb physical rehabilitation robotics.

Physical assistive robotics are oriented to support and improve functional capacities of people. In physical rehabilitation, robots are indeed useful for functional recovery of affected limb. However, there are still open questions related to technological aspects. This work presents a systematic review of upper limb rehabilitation robotics in order to analyze and establish technological challenges and future directions in this area. A bibliometric analysis was performed for the systematic literature review. Literature from the last six years, conducted between August 2020 and May 2021, was reviewed. The methodology for the literature search and a bibliometric analysis of the metadata are presented. After a preliminary search resulted in 820 articles, a total of 66 articles were included. A concurrency network and bibliographic analysis were provided. And an analysis of occurrences, taxonomy, and rehabilitation robotics reported in the literature is presented. This review aims to provide to the scientific community an overview of the state of the art in assistive robotics for upper limb physical rehabilitation. The literature analysis allows access to a gap of unexplored options to define the technological prospects applied to upper limb physical rehabilitation robotics. [ABSTRACT FROM AUTHOR]

Introduction: Robotics uptake in the aerospace industry is low, mainly due to the low-volume/high-accuracy production that aerospace manufacturers require. Furthermore, aerospace manufacturing and assembly sites are often unstructured environments not specifically suitable for robots to operate in. Methods: This paper introduces a robotic visual inspection system using off-the-shelf components able to inspect the mounting holes for wing slat actuators without the need for fixed-coordinate programming; the part just needs to be left within reach of the robot. Our system sets one of the opposed pairs of mounting holes as a reference (the "datum") and then compares the tilt of all other pairs of mounting holes with respect to it. Under the assumption that any deviation in the mounting hole tilt is not systematic but due to normal manufacturing tolerances, our system will either guarantee the correct alignment of all mounting holes or highlight the existence of misaligned holes. Results and Discussion: Computer-vision tilt measurements are performed with an error of below 0.03° using custom optimization for the sub-pixel determination of the center and radius of the mounting holes. The error introduced by the robot's motion from the datum to each of the remaining hole pairs is compensated by moving back to the datum and fixing the orientation again before moving to inspect the next hole pair. This error is estimated to be approximately 0.05°, taking the total tilt error estimation for any mounting hole pair to be 0.08° with respect to the datum. This is confirmed by manually measuring the tilt of the hole pairs using a clock gauge on a calibrated table (not used during normal operation). [ABSTRACT FROM AUTHOR]

Robot-assisted surgery (RAS) has been integrated into clinical practice to overcome several limitations of conventional open or laparoscopic surgery. After the expiration of the long key patent period of Intuitive Surgical, various robotic systems (RSs) have been developed aiming at improving certain characteristics of the first robotic platform, the Da Vinci RS. This narrative review provides an overview of the current RSs used in urology along with the initial results from their application in urologic procedures. Nine robotic platforms are being analyzed regarding their unique characteristics as well as their efficacy, safety, feasibility, and outcomes in urologic, oncological, or non-oncological operations. The main barrier to the wide application of RAS has been the increased cost that refers to both acquisition and maintenance costs. Besides, the health inequality resulting from the lack of expert robotic surgeons and the difficulty of performing robot-assisted procedures in provincial hospitals should be overcome. However, large properly designed comparative studies are required to establish the role of newly introduced RSs. In addition, urologists should keep abreast of new developments and research in robot-assisted urologic procedures. [ABSTRACT FROM AUTHOR]

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This paper proposes a new approach to reconstructing the three-dimensional shapes of target objects. The method is based on object detection using a convolutional neural network, followed by fusing the recognition results with the depth map from a stereo camera. The prospects of applying this new approach are discussed based on the obtained results. [ABSTRACT FROM AUTHOR]

Robotic systems are increasingly being used in healthcare. These systems improve patient care both by freeing healthcare professionals from repetitive tasks and by assisting them with complex procedures. This analysis examines the development and implementation of the use of robotic systems in healthcare. It also examines the application of artificial intelligence (AI), which focuses on the autonomy of robotic systems, enabling them to perform tasks autonomously. It describes the main areas of use of robots in hospitals, gives examples of the main commercial or research robots, and analyzes the main practical and safety issues associated with the use of these systems. Using the main databases, including PubMed, IEEE Xplore, MDPI, ScienceDirect, ACM Digital Library, BioMed Central, Springer, and others, an extensive search for papers related to the topic was conducted. This resulted in 59 papers being identified as eligible for this review. The article concludes with a discussion of future research areas that will ensure the effective integration of autonomous robotic systems in healthcare.

The article analyses the possibilities of using modern technologies in the tactical and specialised training of police officers under martial law. Martial law creates emergency situations when police officers have to work in conditions of increased danger and instability. In such circumstances, the use of modern technologies in tactical and specialised training of police officers becomes extremely important in order to ensure their safety, efficiency and success in performing their tasks. The article outlines the benefits of using technologies such as virtual reality, augmented reality, unmanned aerial vehicles, robotic systems and artificial intelligence. Thus, the main areas of application of modern technologies in the tactical and special training of police officers are: the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers; the use of unmanned aerial vehicles to monitor and obtain information about the situation on the ground without risking the lives of police officers; the use of robotic systems to perform dangerous or difficult tasks, in particular tasks of search and rescue; the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers; the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers. It is noted that the use of modern technologies can increase the effectiveness of police training, reduce the risk to their lives and improve the safety of citizens. The author concludes that the use of modern technologies is an integral part of the tactical and specialised training of police officers under martial law. Technology helps police officers to effectively counter threats, provide security and be successful in their work. The development and improvement of these technologies is an important area for improving the effectiveness of police work under martial law. The introduction of modern technologies in tactical and specialised training of police officers is an important task that will increase the effectiveness of police activities under martial law. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to developing fully automated intelligent control systems for use within production-based organizations, with a specific focus on advancing research into intelligent production systems. This analysis underscores a prevailing deficiency in control operations preceding assembly, where single-purpose control machines are commonly utilized, thus presenting inherent limitations. Conversely, while accurate multipurpose measurement centers exist, they often fail to deliver comprehensive quality control for manufactured parts due to cost and time constraints associated with the measuring process. The primary aim in this study was to develop an intelligent modular control system capable of overseeing the production of diverse components effectively. The modular intelligent control system is designed to meticulously monitor the quality of each module during the pre-assembly phase. By integrating sophisticated sensors, diagnostic tools, and intelligent control mechanisms, this system ensures precise control over module production processes. It facilitates the monitoring of multiple parameters and critical quality features, while integrated sensors and diagnostic methods promptly identify discrepancies and inaccuracies, enabling the swift diagnosis of issues within specific modules. The system's intelligent control algorithms optimize production processes and ensure synchronization among individual modules, thereby ensuring consistent quality and performance. Notably, the implementation of this solution reduces inspection time by an average of 40 to 60% compared to manual inspection methods. Moreover, the system enables the comprehensive archiving of measurement data, eliminating the substantial error rates introduced by human involvement in the inspection process. Furthermore, the system enhances overall project efficiency, predictability, and safety, while allowing for rapid adjustments in order to meet standards and requirements. This innovative approach represents a significant advancement in intelligent control systems for use in production organizations, offering substantial benefits in terms of efficiency, accuracy, and adaptability. [ABSTRACT FROM AUTHOR]

Feeding remains a critical component in rabbit farming. In rabbit production, precise feeding is imperative, given its significant role in augmenting feed efficiency, curtailing farming expenses, reducing disease prevalence and mortality rates, and lessening environmental pollution. This study presents the design and development of a rabbit feeding robot that synergises mobile robotics and mechanical arm technology, aiming for exact feed dispensation within rabbit hutches through a mechanism that precisely quantifies feed volume. The robot developed for this purpose notably minimises feed fragmentation and mitigates stress responses in rabbits, thus facilitating unsupervised, precise feeding tailored to varied dietary needs. Experimental outcomes, garnered within a rabbit hutch, reveal that the mobile robot operated at velocities between 0.05 and 0.20 m s−1. Its navigation and positioning accuracy showed a speed deviation of 1.2 %, a lateral deviation of 5.3 mm, a longitudinal deviation of 7.6 mm, and an angular deviation of 1.1°. The rabbit feeding robot demonstrated a feed quantitative error of 4.3%. At a designated feeding point, the time cycles for dispensing feed across three boxes were recorded as 40.6 s, 50.1 s, and 24.3 s, achieving success rates of 96.3 %, 98.8 %, and 100.0 %, respectively. These results substantiate the practical applicability of the rabbit feeding robot in farming production, thus fostering the progression of intelligent agricultural practices. • The design and development of an unsupervised rabbit feeding robot have been presented. • The robot developed achieves a quantitative error of 4.3% and a low breakage rate. • The feasibility has been validated in a real farming environment. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) in education has gained interest due to its increasing application in various fields. This study explores the potential of AI-based software robots in higher education and their ability to revolutionize educational methodologies. The research purpose is to examine the positive impact of the use of software robots in educational settings. The study focuses on evaluating the prospects of expanding the use of AI-based software robots in higher education. The research uses a combination of observational techniques and practical case studies. It includes an experimental investigation of the basic principles of developing an AI-based robot teacher, with the aim of eventually implementing it in educational processes. The research findings indicate that integrating AI-driven software robots into university education can provide substantial benefits and significant improvements over traditional teaching models. These robots can enhance the educational process and address various developmental challenges. The study highlights the transformative impact of AI-based software robots in modernizing university education. The findings demonstrate the potential of these technologies to reshape the current higher education system. [ABSTRACT FROM AUTHOR]

Introduction: Robotics uptake in the aerospace industry is low, mainly due to the low-volume/high-accuracy production that aerospace manufacturers require. Furthermore, aerospace manufacturing and assembly sites are often unstructured environments not specifically suitable for robots to operate in.Methods: This paper introduces a robotic visual inspection system using off-the-shelf components able to inspect the mounting holes for wing slat actuators without the need for fixed-coordinate programming; the part just needs to be left within reach of the robot. Our system sets one of the opposed pairs of mounting holes as a reference (the “datum”) and then compares the tilt of all other pairs of mounting holes with respect to it. Under the assumption that any deviation in the mounting hole tilt is not systematic but due to normal manufacturing tolerances, our system will either guarantee the correct alignment of all mounting holes or highlight the existence of misaligned holes.Results and Discussion: Computer-vision tilt measurements are performed with an error of below 0.03° using custom optimization for the sub-pixel determination of the center and radius of the mounting holes. The error introduced by the robot’s motion from the datum to each of the remaining hole pairs is compensated by moving back to the datum and fixing the orientation again before moving to inspect the next hole pair. This error is estimated to be approximately 0.05°, taking the total tilt error estimation for any mounting hole pair to be 0.08° with respect to the datum. This is confirmed by manually measuring the tilt of the hole pairs using a clock gauge on a calibrated table (not used during normal operation).

Vision and Robotic technologies are progressively becoming ubiquitous for automating and digitizing quality control in the food industry. This paper examines the crucial role of advanced automation technologies, including versatile or dedicated robotic systems, specialized end-effectors, machine vision, and efficient material handling systems, which collectively enhance food processing efficiency. This paper aspires to provide a high-level technical review on the crucial role of advanced automation technologies, including versatile or dedicated robotic systems, specialized end-effectors, machine vision, and efficient material handling systems, which collectively enhance food processing efficiency. While the manuscript aims to document the various automation sub-systems utilized generally in food processing, it places a particular emphasis on the primary processing phase of food production. Most food products in the primary processing phase exhibit a plethora of complex physical properties and manipulation conditions, making it difficult to reliably automate the various processes. This research aims to outline the contemporary advances and requirements for integrating various automation technologies, to enhance the efficiency and precision of primary food processing. Furthermore, it aspires to serve as a valuable, up-to-date survey and analysis of the latest advances in automation and vision technologies and their capability to automate a food processing line.

This paper aims to provide a global snapshot of concrete 3D-printed buildings and to uncover robotic-oriented large-scale fabrication strategies. Therefore, an extensive internet search and literature review was carried out to investigate 3D-printed buildings. In this study, 154 construction projects with 204 buildings were systematically recorded and evaluated from 2013 up to 2023. Using an exploratory mixed-methods approach and a comparative case study analysis, a total of 88 3D-printed buildings were first evaluated descriptively. Thereafter, different existing printing strategies for in situ, on-site, and off-site production were identified, using an iterative approach. In addition to the geographical distribution, the descriptive evaluation also showed the key players as drivers for the spread of the 3D-printing technology and the correlations between printer type, fabrication strategy, and the building size. With regard to the printing strategy, three different approaches for in situ and off-site fabrication can be defined, depending on the printer types and their characteristics (work size and mobility): print-in-one-go, horizontal or vertical segmentation, and the multi-element vs. full-scaled wall strategy. However, the study showed that the data quality was sometimes difficult due to a lack of information and essential details of the printing process and segmentation.

The modern stage of the development of intelligent robotic systems is characterized by the expansion of fields of application, which is due to autonomous work and decision-making in conditions of uncertainty. The object of research is the system of remote control of robotic systems. During the remote control of robotic systems, problems arise that are associated with the use of wireless communication in real time. The article analyzes software and hardware implementations of various remote control systems suitable for use as part of autonomous robotic systems and analyzes promising microcontroller platforms for implementing a remote control device for a robotic system. A brief review of existing protocols for transmitting control signals using radio communication equipment and microprocessor platforms for the development of embedded systems is performed, among which a solution is selected for research. Several approaches to the control of a robotic system are highlighted – control using a wired connection and corresponding protocols, control via wireless communication or via the Internet, control via general-purpose network protocols. The target platform is chosen and justified, and the S.BUS protocol is analyzed with the provision of an algorithm for obtaining the values of the control channels from the S.BUS package. The structure and algorithm of functioning of the microprocessor remote control system based on the ESP32 microcontroller and the FreeRTOS OS are given. A study of the operation process of the proposed remote control system is carried out, for which it is placed on the chassis of a ground autonomous robotic system with four-wheel drive, and the delay time of the control signal from the receiver to the engine control modules is determined. According to the conducted analysis, the expediency of using specialized radio communication equipment with the S.BUS protocol for controlling executive devices as part of a robotic system, for precise movement control in real time, is shown. [ABSTRACT FROM AUTHOR]

In this paper, we study mechanical optimal control problems on a given Riemannian manifold (Q, g) in which the cost is defined by a general cometric g̃. This investigation is motivated by our studies in robotics, in which we observed that the mathematically natural choice of cometric g̃ = g* – the dual of g – does not always capture the true cost of the motion. We then, first, discuss how to encode the system's torque-based actuators configuration into a cometric g̃. Second, we provide and prove our main theorem, which characterizes the optimal solutions of the problem associated to general triples (Q, g, g̃) in terms of a 4th order differential equation. We also identify a tensor appearing in this equation as the geometric source of "biasing" of the solutions away from ordinary Riemannian splines and geodesics for (Q, g). Finally, we provide illustrative examples and practical demonstration of the biased splines as providing the true optimizers in a concrete robotics system. [ABSTRACT FROM AUTHOR]

In recent years, the integration of artificial intelligence (AI) into robotic systems has opened new horizons across various fields such as industrial production, healthcare, transportation, and space exploration. This article presents how AI enhances robots' capabilities in perception, planning, and executing complex tasks. Deep learning and reinforcement learning algorithms enable robots to analyze sensory data in real-time, make predictions, and make autonomous decisions in dynamic and unpredictable environments. We also address the challenges related to safety, ethics, and human-robot interaction, emphasizing the need for clear regulations and stringent ethical standards. The case study presented illustrates the successful implementation of AI in robotic applications, showcasing the potential of this technology to revolutionize how robots operate and interact with the surrounding world. The conclusions highlight the importance of interdisciplinary collaboration to advance the effective development and deployment of AI in robotics. [ABSTRACT FROM AUTHOR]