Robotics

23 pages, 9845 KiB

Open AccessArticle

An Experimental Investigation of the Dynamic Performances of a High Speed 4-DOF 5R Parallel Robot Using Inverse Dynamics Control

by Paolo Righettini, Roberto Strada, Filippo Cortinovis, Federico Tabaldi, Jasmine Santinelli and Andrea Ginammi

Robotics 2024, 13(3), 54; https://doi.org/10.3390/robotics13030054 - 20 Mar 2024

Cited by 6 | Viewed by 1788

Abstract

High-speed pick-and-place industrial applications often use parallel kinematic robots due to their high stiffness and dynamic performance; furthermore, the latter not only depends on the mechanical characteristics of the robots but also on the control algorithm. The literature shows several theoretical contributions to [...] Read more.

High-speed pick-and-place industrial applications often use parallel kinematic robots due to their high stiffness and dynamic performance; furthermore, the latter not only depends on the mechanical characteristics of the robots but also on the control algorithm. The literature shows several theoretical contributions to such controllers, mainly tested at the simulation level or on simple proof-of-concept laboratory equipment that execute low-speed and simple trajectories. This paper presents an experimental investigation of the dynamic performance of an industrial high-speed 4-DOF 5R parallel robot designed for pick-and-place applications on moving objects. The inverse dynamics control in the task space is used as a control algorithm. The results show the contribution of all the components of the control algorithm to the motor torque, and the inverse dynamics controller performances are discussed also in comparison to those achievable with simpler PD or PID controllers in a joint space. Moreover, the paper shows the controller synthesis from a modern mechatronic point of view, and the effectiveness of the proposed solution for the tracking of complex high-speed trajectories in an industrial application. Full article

(This article belongs to the Special Issue Kinematics and Robot Design VI, KaRD2023)

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15 pages, 1608 KiB

Open AccessArticle

MM-EMOG: Multi-Label Emotion Graph Representation for Mental Health Classification on Social Media

by Rina Carines Cabral, Soyeon Caren Han, Josiah Poon and Goran Nenadic

Robotics 2024, 13(3), 53; https://doi.org/10.3390/robotics13030053 - 18 Mar 2024

Cited by 1 | Viewed by 2368

Abstract

More than 80% of people who commit suicide disclose their intention to do so on social media. The main information we can use in social media is user-generated posts, since personal information is not always available. Identifying all possible emotions in a single [...] Read more.

More than 80% of people who commit suicide disclose their intention to do so on social media. The main information we can use in social media is user-generated posts, since personal information is not always available. Identifying all possible emotions in a single textual post is crucial to detecting the user’s mental state; however, human emotions are very complex, and a single text instance likely expresses multiple emotions. This paper proposes a new multi-label emotion graph representation for social media post-based mental health classification. We first construct a word–document graph tensor to describe emotion-based contextual representation using emotion lexicons. Then, it is trained by multi-label emotions and conducts a graph propagation for harmonising heterogeneous emotional information, and is applied to a textual graph mental health classification. We perform extensive experiments on three publicly available social media mental health classification datasets, and the results show clear improvements. Full article

(This article belongs to the Section AI in Robotics)

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16 pages, 92907 KiB

Open AccessArticle

The Claw: An Avian-Inspired, Large Scale, Hybrid Rigid-Continuum Gripper

by Mary E. Stokes, John K. Mohrmann, Chase G. Frazelle, Ian D. Walker and Ge Lv

Robotics 2024, 13(3), 52; https://doi.org/10.3390/robotics13030052 - 16 Mar 2024

Cited by 1 | Viewed by 2679

Abstract

Most robotic hands have been created at roughly the scale of the human hand, with rigid components forming the core structural elements of the fingers. This focus on the human hand has concentrated attention on operations within the human hand scale, and on [...] Read more.

Most robotic hands have been created at roughly the scale of the human hand, with rigid components forming the core structural elements of the fingers. This focus on the human hand has concentrated attention on operations within the human hand scale, and on the handling of objects suitable for grasping with current robot hands. In this paper, we describe the design, development, and testing of a four-fingered gripper which features a novel combination of actively actuated rigid and compliant elements. The scale of the gripper is unusually large compared to most existing robot hands. The overall goal for the hand is to explore compliant grasping of potentially fragile objects of a size not typically considered. The arrangement of the digits is inspired by the feet of birds, specifically raptors. We detail the motivation for this physical hand structure, its design and operation, and describe testing conducted to assess its capabilities. The results demonstrate the effectiveness of the hand in grasping delicate objects of relatively large size and highlight some limitations of the underlying rigid/compliant hybrid design. Full article

(This article belongs to the Special Issue Intelligent Bionic Robots)

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33 pages, 8086 KiB

Open AccessArticle

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

by Alexandre Athayde, Alexandra Moutinho and José Raúl Azinheira

Robotics 2024, 13(3), 51; https://doi.org/10.3390/robotics13030051 - 16 Mar 2024

Cited by 3 | Viewed by 2130

Abstract

Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the [...] Read more.

Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the problem of stabilizing a tail-sitter when hovering. For this purpose, the first controller is an existing strategy for tail-sitter control obtained from the literature, the second is an application of Nonlinear Dynamic Inversion (NDI), and the last one is its incremental version, INDI. These controllers were implemented and tuned in a simulation in order to stabilize a model of the tail-sitter, complemented by estimation methods that allow the feedback of the necessary variables. These estimators and controllers were then implemented in a microcontroller and validated in a Hardware-in-the-Loop (HITL) scenario with simple maneuvers in vertical flight. Lastly, the developed control solutions were used to stabilize the aircraft in experimental flight while being monitored by a motion capture system. The experimental results allow the validation of the model of the X-Vert and provide a comparison of the performance of the different control solutions, where the INDI presents itself as a robust control strategy with accurate tracking capabilities and less actuator demand. Full article

(This article belongs to the Special Issue UAV Systems and Swarm Robotics)

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17 pages, 2159 KiB

Open AccessReview

Soft Hand Exoskeletons for Rehabilitation: Approaches to Design, Manufacturing Methods, and Future Prospects

by Alexander Saldarriaga, Elkin Iván Gutierrez-Velasquez and Henry A. Colorado

Robotics 2024, 13(3), 50; https://doi.org/10.3390/robotics13030050 - 15 Mar 2024

Viewed by 4603

Abstract

Stroke, the third leading cause of global disability, poses significant challenges to healthcare systems worldwide. Addressing the restoration of impaired hand functions is crucial, especially amid healthcare workforce shortages. While robotic-assisted therapy shows promise, cost and healthcare community concerns hinder the adoption of [...] Read more.

Stroke, the third leading cause of global disability, poses significant challenges to healthcare systems worldwide. Addressing the restoration of impaired hand functions is crucial, especially amid healthcare workforce shortages. While robotic-assisted therapy shows promise, cost and healthcare community concerns hinder the adoption of hand exoskeletons. However, recent advancements in soft robotics and digital fabrication, particularly 3D printing, have sparked renewed interest in this area. This review article offers a thorough exploration of the current landscape of soft hand exoskeletons, emphasizing recent advancements and alternative designs. It surveys previous reviews in the field and examines relevant aspects of hand anatomy pertinent to wearable rehabilitation devices. Furthermore, the article investigates the design requirements for soft hand exoskeletons and provides a detailed review of various soft exoskeleton gloves, categorized based on their design principles. The discussion encompasses simulation-supported methods, affordability considerations, and future research directions. This review aims to benefit researchers, clinicians, and stakeholders by disseminating the latest advances in soft hand exoskeleton technology, ultimately enhancing stroke rehabilitation outcomes and patient care. Full article

(This article belongs to the Section Neurorobotics)

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25 pages, 3493 KiB

Open AccessReview

Intelligent Robotics in Pediatric Cooperative Neurorehabilitation: A Review

by Elishai Ezra Tsur and Odelia Elkana

Robotics 2024, 13(3), 49; https://doi.org/10.3390/robotics13030049 - 14 Mar 2024

Cited by 1 | Viewed by 2846

Abstract

The landscape of neurorehabilitation is undergoing a profound transformation with the integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing need for advancements in pediatric neurorehabilitation and underscores the pivotal role of AI-driven robotics in addressing existing gaps. By leveraging AI [...] Read more.

The landscape of neurorehabilitation is undergoing a profound transformation with the integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing need for advancements in pediatric neurorehabilitation and underscores the pivotal role of AI-driven robotics in addressing existing gaps. By leveraging AI technologies, robotic systems can transcend the limitations of preprogrammed guidelines and adapt to individual patient needs, thereby fostering patient-centric care. This review explores recent strides in social and diagnostic robotics, physical therapy, assistive robotics, smart interfaces, and cognitive training within the context of pediatric neurorehabilitation. Furthermore, it examines the impact of emerging AI techniques, including artificial emotional intelligence, interactive reinforcement learning, and natural language processing, on enhancing cooperative neurorehabilitation outcomes. Importantly, the review underscores the imperative of responsible AI deployment and emphasizes the significance of unbiased, explainable, and interpretable models in fostering adaptability and effectiveness in pediatric neurorehabilitation settings. In conclusion, this review provides a comprehensive overview of the evolving landscape of AI-driven robotics in pediatric neurorehabilitation and offers valuable insights for clinicians, researchers, and policymakers. Full article

(This article belongs to the Special Issue Neurorehabilitation Robotics: Recent Trends and Novel Applications)

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19 pages, 7907 KiB

Open AccessArticle

Trajectory Tracking and Disturbance Rejection Performance Analysis of Classical and Advanced Controllers for a SCORBOT Robot

by John Kern, Claudio Urrea, Humberto Verdejo, Rayko Agramonte and Cristhian Becker

Robotics 2024, 13(3), 48; https://doi.org/10.3390/robotics13030048 - 13 Mar 2024

Cited by 1 | Viewed by 1709

Abstract

This work presents the design and assessment of four control schemes for the monitoring and regulation of joint trajectories applied in the dynamic model of a SCORBOT-ER V plus robot, which includes the dynamics of the actuators, and the estimation of the friction [...] Read more.

This work presents the design and assessment of four control schemes for the monitoring and regulation of joint trajectories applied in the dynamic model of a SCORBOT-ER V plus robot, which includes the dynamics of the actuators, and the estimation of the friction forces present within the joints. The two classical control strategies calculated torque and PID, and the two advanced control strategies, fuzzy and predictive, are considered. In the latter case, a gravitational compensation stage is incorporated, as well as the inverse models of the motors and the transmissions of belt movement for each joint. Computational tests are performed by applying an external step-type disturbance to the third joint of the robot. Finally, an evaluation of the results obtained is presented through trajectory curves, joint errors, and the three performance indexes residual mean square, residual standard deviation, and index of agreement. Full article

(This article belongs to the Section Intelligent Robots and Mechatronics)

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15 pages, 7475 KiB

Open AccessArticle

A Deep Learning Approach to Merge Rule-Based and Human-Operated Camera Control for Teleoperated Robotic Systems

by Luay Jawad, Arshdeep Singh-Chudda, Abhishek Shankar and Abhilash Pandya

Robotics 2024, 13(3), 47; https://doi.org/10.3390/robotics13030047 - 11 Mar 2024

Viewed by 1794

Abstract

Controlling a laparoscopic camera during robotic surgery represents a multifaceted challenge, demanding considerable physical and cognitive exertion from operators. While manual control presents the advantage of enabling optimal viewing angles, it is offset by its taxing nature. In contrast, current autonomous camera systems [...] Read more.

Controlling a laparoscopic camera during robotic surgery represents a multifaceted challenge, demanding considerable physical and cognitive exertion from operators. While manual control presents the advantage of enabling optimal viewing angles, it is offset by its taxing nature. In contrast, current autonomous camera systems offer predictability in tool tracking but are often rigid, lacking the adaptability of human operators. This research investigates the potential of two distinct network architectures: a dense neural network (DNN) and a recurrent network (RNN), both trained using a diverse dataset comprising autonomous and human-driven camera movements. A comparative assessment of network-controlled, autonomous, and human-operated camera systems is conducted to gauge network efficacies. While the dense neural network exhibits proficiency in basic tool tracking, it grapples with inherent architectural limitations that hinder its ability to master the camera’s zoom functionality. In stark contrast, the recurrent network excels, demonstrating a capacity to sufficiently replicate the behaviors exhibited by a mixture of both autonomous and human-operated methods. In total, 96.8% of the dense network predictions had up to a one-centimeter error when compared to the test datasets, while the recurrent network achieved a 100% sub-millimeter testing error. This paper trains and evaluates neural networks on autonomous and human behavior data for camera control. Full article

(This article belongs to the Special Issue Robots and Artificial Intelligence for a Better Future of Health Care)

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15 pages, 6675 KiB

Open AccessArticle

Development of Local Path Planning Using Selective Model Predictive Control, Potential Fields, and Particle Swarm Optimization

by Mingeuk Kim, Minyoung Lee, Byeongjin Kim and Moohyun Cha

Robotics 2024, 13(3), 46; https://doi.org/10.3390/robotics13030046 - 8 Mar 2024

Cited by 2 | Viewed by 2380

Abstract

This paper focuses on the real-time obstacle avoidance and safe navigation of autonomous ground vehicles (AGVs). It introduces the Selective MPC-PF-PSO algorithm, which includes model predictive control (MPC), Artificial Potential Fields (APFs), and particle swarm optimization (PSO). This approach involves defining multiple sets [...] Read more.

This paper focuses on the real-time obstacle avoidance and safe navigation of autonomous ground vehicles (AGVs). It introduces the Selective MPC-PF-PSO algorithm, which includes model predictive control (MPC), Artificial Potential Fields (APFs), and particle swarm optimization (PSO). This approach involves defining multiple sets of coefficients for adaptability to the surrounding environment. The simulation results demonstrate that the algorithm is appropriate for generating obstacle avoidance paths. The algorithm was implemented on the ROS platform using NVIDIA’s Jetson Xavier, and driving experiments were conducted with a steer-type AGV. Through measurements of computation time and real obstacle avoidance experiments, it was shown to be practical in the real world. Full article

(This article belongs to the Special Issue Autonomous Navigation of Mobile Robots in Unstructured Environments)

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18 pages, 2549 KiB

Open AccessArticle

Design and Analysis of Tracked Stair-Climbing Robot Using Innovative Suspension System

by Antonio Pappalettera, Giulio Reina and Giacomo Mantriota

Robotics 2024, 13(3), 45; https://doi.org/10.3390/robotics13030045 - 7 Mar 2024

Cited by 1 | Viewed by 2844

Abstract

Obstacle-crossing and stair-climbing abilities are crucial to the performance of mobile robots for urban environment mobility. This paper proposes a tracked stair-climbing robot with two bogie-like suspensions to overcome architectural barriers. After a general introduction to stair-climbing robots, the “XXbot” concept is presented. [...] Read more.

Obstacle-crossing and stair-climbing abilities are crucial to the performance of mobile robots for urban environment mobility. This paper proposes a tracked stair-climbing robot with two bogie-like suspensions to overcome architectural barriers. After a general introduction to stair-climbing robots, the “XXbot” concept is presented. We developed a special model that helps us figure out how a system will move based on the shape of the ground it is on. Then, stair-climbing simulations were performed with the multibody software MSC-Adams and the results are presented. This shows that the robot can be used in many different ways, such as stair-climbing wheelchair platforms. Full article

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13 pages, 837 KiB

Open AccessArticle

Investigation of the Effectiveness of the Robotic ReStore Soft Exoskeleton in the Development of Early Mobilization, Walking, and Coordination of Stroke Patients: A Randomized Clinical Trial

by Szilvia Kóra, Adrienn Bíró, Nándor Prontvai, Mónika Androsics, István Drotár, Péter Prukner, Tamás Haidegger, Klaudia Széphelyi and József Tollár

Robotics 2024, 13(3), 44; https://doi.org/10.3390/robotics13030044 - 5 Mar 2024

Cited by 1 | Viewed by 3235

Abstract

Medical robotics nowadays can prevent, treat, or alleviate numerous severe conditions, including the dire consequences of stroke. Our objective was to determine the effect of employing a robotic soft exoskeleton in therapy on the development of the early mobilization, gait, and coordination in [...] Read more.

Medical robotics nowadays can prevent, treat, or alleviate numerous severe conditions, including the dire consequences of stroke. Our objective was to determine the effect of employing a robotic soft exoskeleton in therapy on the development of the early mobilization, gait, and coordination in stroke patients. The ReStore™ Soft Exo-Suit, a wearable exosuit developed by a leading company with exoskeleton technology, was utilized. It is a powered, lightweight device intended for use in stroke rehabilitation for people with lower limb disability. We performed a randomized clinical intervention, using a before–after trial design in a university hospital setting. A total of 48 patients with a history of stroke were included, of whom 39 were randomized and 30 completed the study. Interventions: Barthel Index and modified Rankin scale (mRS) patients were randomly assigned to a non-physical intervention control (n = 9 of 39 completed, 30 withdrew before baseline testing), or to a high-intensity agility program (15 sessions, 5 weeks, n = 30 completed). The main focus of assessment was on the Modified Rankin Scale. Additionally, we evaluated secondary factors including daily life functionality, five dimensions of health-related quality of life, the Beck depression inventory, the 6 min walk test (6MWT), the Berg Balance Scale (BBS), and static balance (center of pressure). The Robot-Assisted Gait Therapy (ROB/RAGT) program led to significant improvements across various measures, including a 37% improvement in Barthel Index scores, a 56% increase in 10 m walking speed, and a 68% improvement in 6 min walking distance, as well as notable enhancements in balance and stability. Additionally, the intervention group demonstrated significant gains in all these aspects compared to the control group. In conclusion, the use of robotic therapy can be beneficial in stroke rehabilitation. These devices support the restoration and improvement of movement in various ways and contribute to restoring balance and stability. Full article

(This article belongs to the Special Issue AI for Robotic Exoskeletons and Prostheses)

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30 pages, 3362 KiB

Open AccessArticle

Got It? Comparative Ergonomic Evaluation of Robotic Object Handover for Visually Impaired and Sighted Users

by Dorothea Langer, Franziska Legler, Pia Diekmann, André Dettmann, Sebastian Glende and Angelika C. Bullinger

Robotics 2024, 13(3), 43; https://doi.org/10.3390/robotics13030043 - 5 Mar 2024

Viewed by 1887

Abstract

The rapidly growing research on the accessibility of digital technologies has focused on blind or visually impaired (BVI) users. However, the field of human–robot interaction has largely neglected the needs of BVI users despite the increasing integration of assistive robots into daily life [...] Read more.

The rapidly growing research on the accessibility of digital technologies has focused on blind or visually impaired (BVI) users. However, the field of human–robot interaction has largely neglected the needs of BVI users despite the increasing integration of assistive robots into daily life and their potential benefits for our aging societies. One basic robotic capability is object handover. Robots assisting BVI users should be able to coordinate handovers without eye contact. This study gathered insights on the usability of human–robot handovers, including 20 BVI and 20 sighted participants. In a standardized experiment with a mixed design, a handover robot prototype equipped with a voice user interface and haptic feedback was evaluated. The robot handed over everyday objects (i) by placing them on a table and (ii) by allowing for midair grasping. The usability target was met, and all user groups reported a positive user experience. In total, 97.3% of all handovers were successful. The qualitative feedback showed an appreciation for the clear communication of the robot’s actions and the handover reliability. However, the duration of the handover was seen as a critical issue. According to all subjective criteria, the BVI participants showed higher variances compared to the sighted participants. Design recommendations for improving robotic handovers equally supporting both user groups are given. Full article

(This article belongs to the Special Issue Human Factors in Human–Robot Interaction)

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24 pages, 1934 KiB

Open AccessArticle

Towards Industrial Robots’ Maturity: An Italian Case Study

by Francesco Aggogeri, Nicola Pellegrini and Claudio Taesi

Robotics 2024, 13(3), 42; https://doi.org/10.3390/robotics13030042 - 3 Mar 2024

Cited by 3 | Viewed by 2408

Abstract

This paper aims to investigate the impact of industrial robotics, examining the process integration in a sample of +600 companies located in the Province of Brescia, an intensive industrial area in the North of Italy. Through a detailed economic investigation, this study analyses [...] Read more.

This paper aims to investigate the impact of industrial robotics, examining the process integration in a sample of +600 companies located in the Province of Brescia, an intensive industrial area in the North of Italy. Through a detailed economic investigation, this study analyses the adoption of robotic solutions in companies of varying sizes, using a survey and financial databases to investigate the most used types of robots, their applications, the impacts at the operational and personnel level, and the companies’ growth (sales, employees, other). The results highlight a significant presence of robotic solutions, particularly articulated robots, in the large companies involved. Robotics diffusion positively correlates with significant improvements in terms of productivity and quality. The introduction of robots is associated with increased corporate growth indicators, including staff expansion. Large companies demonstrate a superior ability to adapt to these technologies, supported by more significant financial resources and a wide range of internal competencies for managing robots. Furthermore, large companies proactively hire qualified personnel or initiate internal training courses. Small and medium-sized enterprises (SMEs), although currently less equipped with robotic technologies, exhibit a significant interest in future adoption, highlighting the opportunity for growth and innovation. The results suggest that integrating robotics in the manufacturing sector not only constitutes an effective means to enhance operational performance but also acts as a catalyst for developing human capital and strengthening the local economy. Full article

(This article belongs to the Section Industrial Robots and Automation)

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15 pages, 7863 KiB

Open AccessArticle

Double-Layer RRT* Objective Bias Anytime Motion Planning Algorithm

by Hamada Esmaiel, Guolin Zhao, Zeyad A. H. Qasem, Jie Qi and Haixin Sun

Robotics 2024, 13(3), 41; https://doi.org/10.3390/robotics13030041 - 1 Mar 2024

Cited by 1 | Viewed by 1900

Abstract

This paper proposes a double-layer structure RRT* algorithm based on objective bias called DOB-RRT*. The algorithm adopts an initial path with an online optimization structure for motion planning. The first layer of RRT* introduces a feedback-based objective bias strategy with segment forward pruning [...] Read more.

This paper proposes a double-layer structure RRT* algorithm based on objective bias called DOB-RRT*. The algorithm adopts an initial path with an online optimization structure for motion planning. The first layer of RRT* introduces a feedback-based objective bias strategy with segment forward pruning processing to quickly obtain a smooth initial path. The second layer of RRT* uses the heuristics of the initial tree structure to optimize the path by using reverse maintenance strategies. Compared with conventional RRT and RRT* algorithms, the proposed algorithm can obtain the initial path with high quality, and it can quickly converge to the progressive optimal path during the optimization process. The performance of the proposed algorithm is effectively evaluated and tested in real experiments on an actual wheeled robotic vehicle running ROS Kinetic in a real environment. Full article

(This article belongs to the Section Sensors and Control in Robotics)

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15 pages, 2715 KiB

Open AccessArticle

Real-Time Multi-Robot Mission Planning in Cluttered Environment

by Zehui Lu, Tianyu Zhou and Shaoshuai Mou

Robotics 2024, 13(3), 40; https://doi.org/10.3390/robotics13030040 - 28 Feb 2024

Cited by 2 | Viewed by 2109

Abstract

Addressing a collision-aware multi-robot mission planning problem, which involves task allocation and path-finding, poses a significant difficulty due to the necessity for real-time computational efficiency, scalability, and the ability to manage both static and dynamic obstacles and tasks within a complex environment. This [...] Read more.

Addressing a collision-aware multi-robot mission planning problem, which involves task allocation and path-finding, poses a significant difficulty due to the necessity for real-time computational efficiency, scalability, and the ability to manage both static and dynamic obstacles and tasks within a complex environment. This paper introduces a parallel real-time algorithm aimed at overcoming these challenges. The proposed algorithm employs an approximation-based partitioning mechanism to partition the entire unassigned task set into several subsets. This approach decomposes the original problem into a series of single-robot mission planning problems. To validate the effectiveness of the proposed method, both numerical and hardware experiments are conducted, involving dynamic obstacles and tasks. Additionally, comparisons in terms of optimality and scalability against an existing method are provided, showcasing its superior performance across both metrics. Furthermore, a computational burden analysis is conducted to demonstrate the consistency of our method with the observations derived from these comparisons. Finally, the optimality gap between the proposed method and the global optima in small-size problems is demonstrated. Full article

(This article belongs to the Special Issue Decision-Making and Control under Uncertainties for Robotic and Autonomous Systems)

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16 pages, 11050 KiB

Open AccessArticle

A Control Interface for Autonomous Positioning of Magnetically Actuated Spheres Using an Artificial Neural Network

by Victor Huynh, Basam Mutawak, Minh Quan Do, Elizabeth A. Ankrah, Pouya Kassaeiyan, Irving N. Weinberg, Nathalia Peixoto, Qi Wei and Lamar O. Mair

Robotics 2024, 13(3), 39; https://doi.org/10.3390/robotics13030039 - 28 Feb 2024

Viewed by 1790

Abstract

Electromagnet arrays show significant potential in the untethered guidance of particles, devices, and eventually robots. However, complications in obtaining accurate models of electromagnetic fields pose challenges for precision control. Manipulation often requires the reduced-order modeling of physical systems, which may be computationally complex [...] Read more.

Electromagnet arrays show significant potential in the untethered guidance of particles, devices, and eventually robots. However, complications in obtaining accurate models of electromagnetic fields pose challenges for precision control. Manipulation often requires the reduced-order modeling of physical systems, which may be computationally complex and may still not account for all possible system dynamics. Additionally, control schemes capable of being applied to electromagnet arrays of any configuration may significantly expand the usefulness of any control approach. In this study, we developed a data-driven approach to the magnetic control of a neodymium magnets (NdFeB magnetic sphere) using a simple, highly constrained magnetic actuation architecture. We developed and compared two regression-based schemes for controlling the NdFeB sphere in the workspace of a four-coil array of electromagnets. We obtained averaged submillimeter positional control (0.85 mm) of a NdFeB hard magnetic sphere in a 2D plane using a controller trained using a single-layer, five-input regression neural network with a single hidden layer. Full article

(This article belongs to the Special Issue Applications of Neural Networks in Robot Control)

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17 pages, 8463 KiB

Open AccessArticle

Design of a Wheelchair-Mounted Robotic Arm for Feeding Assistance of Upper-Limb Impaired Patients

by Simone Leone, Luigi Giunta, Vincenzo Rino, Simone Mellace, Alessio Sozzi, Francesco Lago, Elio Matteo Curcio, Doina Pisla and Giuseppe Carbone

Robotics 2024, 13(3), 38; https://doi.org/10.3390/robotics13030038 - 26 Feb 2024

Cited by 2 | Viewed by 3296

Abstract

This paper delineates the design and realization of a Wheelchair-Mounted Robotic Arm (WMRA), envisioned as an autonomous assistance apparatus for individuals encountering motor difficulties and/or upper limb paralysis. The proposed design solution is based on employing a 3D printing process coupled with optimization [...] Read more.

This paper delineates the design and realization of a Wheelchair-Mounted Robotic Arm (WMRA), envisioned as an autonomous assistance apparatus for individuals encountering motor difficulties and/or upper limb paralysis. The proposed design solution is based on employing a 3D printing process coupled with optimization design techniques to achieve a cost-oriented and user-friendly solution. The proposed design is based on utilizing commercial Arduino control hardware. The proposed device has been named Pick&Eat. The proposed device embodies reliability, functionality, and cost-effectiveness, and features a modular structure housing a 4-degrees-of-freedom robotic arm with a fixing frame that can be attached to commercial wheelchairs. The arm is integrated with an interchangeable end-effector facilitating the use of various tools such as spoons or forks tailored to different food types. Electrical and sensor components were meticulously designed, incorporating sensors to ensure user safety throughout operations. Smooth and secure operations are achieved through a sequential procedure that is depicted in a specific flowchart. Experimental tests have been carried out to demonstrate the engineering feasibility and effectiveness of the proposed design solution as an innovative assistive solution for individuals grappling with upper limb impairment. Its capacity to aid patients during the eating process holds promise for enhancing their quality of life, particularly among the elderly and those with disabilities. Full article

(This article belongs to the Special Issue Recent Trends and Advances on Robotics and Mechatronics within the IFToMM Technical Committee on Robotics and Mechatronics)

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22 pages, 6247 KiB

Open AccessArticle

Advanced Path Planning for Autonomous Street-Sweeper Fleets under Complex Operational Conditions

by Tyler Parsons, Farhad Baghyari, Jaho Seo, Wongun Kim and Myeonggyu Lee

Robotics 2024, 13(3), 37; https://doi.org/10.3390/robotics13030037 - 25 Feb 2024

Cited by 1 | Viewed by 2200

Abstract

In recent years, autonomous mobile platforms have seen an increase in usage in several applications. One of which is street-sweeping. Although street-sweeping is a necessary process due to health and cleanliness, fleet operations are difficult to plan optimally. Since each vehicle has several [...] Read more.

In recent years, autonomous mobile platforms have seen an increase in usage in several applications. One of which is street-sweeping. Although street-sweeping is a necessary process due to health and cleanliness, fleet operations are difficult to plan optimally. Since each vehicle has several constraints (battery, debris, and water), path planning becomes increasingly difficult to perform manually. Additionally, in real-world applications vehicles may become inactive due to a breakdown, which requires real-time scheduling technology to update the paths for the remaining vehicles. In this paper, the fleet street-sweeping problem can be solved using the proposed lower-level and higher-level path generation methods. For the lower level, a Smart Selective Navigator algorithm is proposed, and a modified genetic algorithm is used for the higher-level path planning. A case study was presented for Uchi Park, South Korea, where the proposed methodology was validated. Specifically, results generated from the ideal scenario (all vehicles operating) were compared to the breakdown scenario, where little to no difference in the overall statistics was observed. Additionally, the lower-level path generation could yield solutions with over 94% area coverage. Full article

(This article belongs to the Section Intelligent Robots and Mechatronics)

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15 pages, 3678 KiB

Open AccessArticle

The Impact of Changing Collaborative Workplace Parameters on Assembly Operation Efficiency

by Klemen Kovič, Aljaž Javernik, Robert Ojsteršek and Iztok Palčič

Robotics 2024, 13(3), 36; https://doi.org/10.3390/robotics13030036 - 23 Feb 2024

Cited by 1 | Viewed by 1706

Abstract

Human–robot collaborative systems bring several benefits in using human and robot capabilities simultaneously. One of the critical questions is the impact of these systems on production process efficiency. The search for high-level efficiency is severely dependent on collaborative robot characteristics and motion parameters, [...] Read more.

Human–robot collaborative systems bring several benefits in using human and robot capabilities simultaneously. One of the critical questions is the impact of these systems on production process efficiency. The search for high-level efficiency is severely dependent on collaborative robot characteristics and motion parameters, and the ability of humans to adjust to changing circumstances. Therefore, our research analyzes the effect of the changing collaborative robot motion parameters, acoustic parameters and visual factors in a specific assembly operation, where efficiency is measured through operation times. To conduct our study, we designed a digital twin-based model and a laboratory environment experiment in the form of a collaborative workplace. The results show that changing the motion, acoustic and visual parameters of the collaborative workplace impact the assembly process efficiency significantly. Full article

(This article belongs to the Special Issue Digital Twin-Based Human–Robot Collaborative Systems)

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32 pages, 17080 KiB

Open AccessArticle

User Study to Validate the Performance of an Offline Robot Programming Method That Enables Robot-Independent Kinesthetic Instruction through the Use of Augmented Reality and Motion Capturing

by Fabian Müller, Michael Koch and Alexander Hasse

Robotics 2024, 13(3), 35; https://doi.org/10.3390/robotics13030035 - 23 Feb 2024

Viewed by 1783

Abstract

The paper presents a novel offline programming (OLP) method based on programming by demonstration (PbD), which has been validated through user study. PbD is a programming method that involves physical interaction with robots, and kinesthetic teaching (KT) is a commonly used online programming [...] Read more.

The paper presents a novel offline programming (OLP) method based on programming by demonstration (PbD), which has been validated through user study. PbD is a programming method that involves physical interaction with robots, and kinesthetic teaching (KT) is a commonly used online programming method in industry. However, online programming methods consume significant robot resources, limiting the speed advantages of PbD and emphasizing the need for an offline approach. The method presented here, based on KT, uses a virtual representation instead of a physical robot, allowing independent programming regardless of the working environment. It employs haptic input devices to teach a simulated robot in augmented reality and uses automatic path planning. A benchmarking test was conducted to standardize equipment, procedures, and evaluation techniques to compare different PbD approaches. The results indicate a

47 %

decrease in programming time when compared to traditional KT methods in established industrial systems. Although the accuracy is not yet at the level of industrial systems, users have shown rapid improvement, confirming the learnability of the system. User feedback on the perceived workload and the ease of use was positive. In conclusion, this method has potential for industrial use due to its learnability, reduction in robot downtime, and applicability across different robot sizes and types. Full article

(This article belongs to the Special Issue Digital Twin-Based Human–Robot Collaborative Systems)

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15 pages, 432 KiB

Open AccessSystematic Review

Systematic Literature Review on Hybrid Robotic Vehicles

by Diogo F. Gomes and Vítor H. Pinto

Robotics 2024, 13(3), 34; https://doi.org/10.3390/robotics13030034 - 23 Feb 2024

Viewed by 2135

Abstract

Autonomous vehicles are a continuously rising technology in several industry sectors. Examples of these technologies lie in the advances in self-driving cars and can be linked to extraterrestrial exploration, such as NASA’s Mars Exploration Rovers. These systems present a leading methodology allowing for [...] Read more.

Autonomous vehicles are a continuously rising technology in several industry sectors. Examples of these technologies lie in the advances in self-driving cars and can be linked to extraterrestrial exploration, such as NASA’s Mars Exploration Rovers. These systems present a leading methodology allowing for increased task performance and capabilities, which are no longer limited to active human support. However, these robotic systems may vary in shape, size, locomotion capabilities, and applications. As such, this report presents a systematic literature review (SLR) regarding hybrid autonomous robotic vehicles focusing on leg–wheel locomotion. During this systematic review of the literature, a considerable number of articles were extracted from four different databases. After the selection process, a filtered sample was reviewed. A brief description of each document can be found throughout this report. Full article

(This article belongs to the Section Agricultural and Field Robotics)

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Robotics, Volume 13, Issue 3 (March 2024) – 21 articles

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