Journal Description
Robotics
Robotics
is an international, peer-reviewed, open access journal on robotics published monthly online by MDPI. The IFToMM is affiliated with Robotics and its members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), dblp, Inspec, and other databases.
- Journal Rank: CiteScore - Q1 (Control and Optimization)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.3 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.7 (2022);
5-Year Impact Factor:
3.7 (2022)
Latest Articles
Robotics and AI for Precision Agriculture
Robotics 2024, 13(4), 64; https://doi.org/10.3390/robotics13040064 - 20 Apr 2024
Abstract
To meet the rising food demand of a world population predicted to reach 9 [...]
Full article
(This article belongs to the Special Issue Robotics and AI for Precision Agriculture)
Open AccessArticle
Safe Reinforcement Learning for Arm Manipulation with Constrained Markov Decision Process
by
Patrick Adjei, Norman Tasfi, Santiago Gomez-Rosero and Miriam A. M. Capretz
Robotics 2024, 13(4), 63; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040063 - 18 Apr 2024
Abstract
In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible scenarios. Reinforcement learning has shown promise in robotics due
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In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible scenarios. Reinforcement learning has shown promise in robotics due to its superior adaptability over traditional logic. However, the exploratory nature of reinforcement learning can jeopardize safety. This paper addresses the challenges in planning trajectories for robotic arm manipulators in dynamic environments. In addition, this paper highlights the pitfalls of multiple reward compositions that are susceptible to reward hacking. A novel method with a simplified reward and constraint formulation is proposed. This enables the robot arm to avoid a nonstationary obstacle that never resets, enhancing operational safety. The proposed approach combines scalarized expected returns with a constrained Markov decision process through a Lagrange multiplier, resulting in better performance. The scalarization component uses the indicator cost function value, directly sampled from the replay buffer, as an additional scaling factor. This method is particularly effective in dynamic environments where conditions change continually, as opposed to approaches relying solely on the expected cost scaled by a Lagrange multiplier.
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(This article belongs to the Section AI in Robotics)
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Designing Digital Twins of Robots Using Simscape Multibody
by
Giovanni Boschetti and Teresa Sinico
Robotics 2024, 13(4), 62; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040062 - 14 Apr 2024
Abstract
Digital twins of industrial and collaborative robots are widely used to evaluate and predict the behavior of manipulators under different control strategies. However, these digital twins often employ simplified mathematical models that do not fully describe their dynamics. In this paper, we present
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Digital twins of industrial and collaborative robots are widely used to evaluate and predict the behavior of manipulators under different control strategies. However, these digital twins often employ simplified mathematical models that do not fully describe their dynamics. In this paper, we present the design of a high-fidelity digital twin of a six degrees-of-freedom articulated robot using Simscape Multibody, a Matlab toolbox that allows the design of robotic manipulators in a rather intuitive and user-friendly manner. This robot digital twin includes joint friction, transmission gears, and electric actuators dynamics. After assessing the dynamic accuracy of the Simscape model, we used it to test a computed torque control scheme, proving that this model can be reliably used in simulations with different aims, such as validating control schemes, evaluating collaborative functions or minimizing power consumption.
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(This article belongs to the Special Issue Digital Twin-Based Human–Robot Collaborative Systems)
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The Town Crier: A Use-Case Design and Implementation for a Socially Assistive Robot in Retirement Homes
by
Ana Iglesias, Raquel Viciana, José Manuel Pérez-Lorenzo, Karine Lan Hing Ting, Alberto Tudela, Rebeca Marfil, Malak Qbilat, Antonio Hurtado, Antonio Jerez and Juan Pedro Bandera
Robotics 2024, 13(4), 61; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040061 - 09 Apr 2024
Abstract
The use of new assistive technologies in general, and Socially Assistive Robots (SARs) in particular, is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due
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The use of new assistive technologies in general, and Socially Assistive Robots (SARs) in particular, is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due to design processes that insufficiently take into account the needs, preferences and values of intended users. Other issues are related to the currently very limited amount of long-term evaluations, performed in real-world settings, for SARs. This study presents the results of two regional projects that consider as a starting hypothesis that the assessment in controlled environments and/or with short exposures may not be enough in the design of an SAR deployed in a retirement home and the necessity of designing for and with users. Thus, the proposed methodology has focused on use-cases definitions that follow a human-centred and participatory design approach. The main goals have been facilitating system acceptance and attachment by involving stakeholders in the robots design and evaluation, overcoming usage barriers and considering user’s needs integration. The implementation of the first use-case deployed and the two-phase pilot test performed in a retirement home are presented. In particular, a detailed description of the interface redesign process based on improving a basic prototype with users’ feedback and recommendations is presented, together with the main results of a formal evaluation that has highlighted the impact of changes and improvements addressed in the first redesign loop of the system.
Full article
(This article belongs to the Special Issue Social Robots for the Human Well-Being)
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A Framework for Modeling, Optimization, and Musculoskeletal Simulation of an Elbow–Wrist Exosuit
by
Ali KhalilianMotamed Bonab, Domenico Chiaradia, Antonio Frisoli and Daniele Leonardis
Robotics 2024, 13(4), 60; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040060 - 06 Apr 2024
Abstract
The light weight and compliance of exosuits are valuable benefits not present rigid exoskeleton devices, yet these intriguing features make it challenging to properly model and simulate their interaction with the musculoskeletal system. Tendon-driven exosuits adopt an electrical motor combined with pulleys and
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The light weight and compliance of exosuits are valuable benefits not present rigid exoskeleton devices, yet these intriguing features make it challenging to properly model and simulate their interaction with the musculoskeletal system. Tendon-driven exosuits adopt an electrical motor combined with pulleys and cable transmission in the actuation stage. An important aspect of the design of these systems for the load transfer efficacy and comfort of the user is the anchor point positioning. In this paper, we propose a framework, whose first purpose is as a design methodology for the synthesis of an exosuit device, achieved by optimizing the anchor point location. The optimization procedure finds the best 3D position of the anchor points based on the interaction forces between the exosuit and the upper arm. The computation of the forces is based on the combination of a mathematical model of a wrist–elbow exosuit and a dynamic model of the upper arm. Its second purpose is the simulation of the kinematic and physiological effects of the interaction between the arm, the exosuit, and the complex upper limb musculoskeletal system. It offers insights into muscular and exoskeleton loading during operation. The presented experiments involve the development and validation of personalized musculoskeletal models, with kinematic, anthropometric, and electromyographic data measured in a load-lifting task. Simulation of the exosuit operation—coupled with the musculoskeletal model—showed the efficacy of the suit in assisting the wrist and elbow muscles and provided interesting highlights about the impact of the assistance on shoulder muscles. Finally, we provide a possible design of an elbow and wrist exosuit based on the optimized results.
Full article
(This article belongs to the Special Issue AI for Robotic Exoskeletons and Prostheses)
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Open AccessArticle
Bimanual Telemanipulation Framework Utilising Multiple Optically Localised Cooperative Mobile Manipulators
by
Christopher Peers and Chengxu Zhou
Robotics 2024, 13(4), 59; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040059 - 01 Apr 2024
Abstract
Bimanual manipulation is valuable for its potential to provide robots in the field with increased capabilities when interacting with environments, as well as broadening the number of possible manipulation actions available. However, for a robot to perform bimanual manipulation, the system must have
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Bimanual manipulation is valuable for its potential to provide robots in the field with increased capabilities when interacting with environments, as well as broadening the number of possible manipulation actions available. However, for a robot to perform bimanual manipulation, the system must have a capable control framework to localise and generate trajectories and commands for each sub-system to allow for successful cooperative manipulation as well as sufficient control over each individual sub-system. The proposed method suggests using multiple mobile manipulator platforms coupled through the use of an optical tracking localisation method to act as a single bimanual manipulation system. The framework’s performance relies on the accuracy of the localisation. As commands are primarily high-level, it is possible to use any number and combination of mobile manipulators and fixed manipulators within this framework. We demonstrate the functionality of this system through tests in a Pybullet simulation environment using two different omnidirectional mobile manipulators, as well a real-life experiment using two quadrupedal manipulators.
Full article
(This article belongs to the Special Issue Legged Robots into the Real World, Volume II)
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Exploring Saliency for Learning Sensory-Motor Contingencies in Loco-Manipulation Tasks
by
Elisa Stefanini, Gianluca Lentini, Giorgio Grioli, Manuel Giuseppe Catalano and Antonio Bicchi
Robotics 2024, 13(4), 58; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040058 - 01 Apr 2024
Abstract
The objective of this paper is to propose a framework for a robot to learn multiple Sensory-Motor Contingencies from human demonstrations and reproduce them. Sensory-Motor Contingencies are a concept that describes intelligent behavior of animals and humans in relation to their environment. They
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The objective of this paper is to propose a framework for a robot to learn multiple Sensory-Motor Contingencies from human demonstrations and reproduce them. Sensory-Motor Contingencies are a concept that describes intelligent behavior of animals and humans in relation to their environment. They have been used to design control and planning algorithms for robots capable of interacting and adapting autonomously. However, enabling a robot to autonomously develop Sensory-Motor Contingencies is challenging due to the complexity of action and perception signals. This framework leverages tools from Learning from Demonstrations to have the robot memorize various sensory phases and corresponding motor actions through an attention mechanism. This generates a metric in the perception space, used by the robot to determine which sensory-motor memory is contingent to the current context. The robot generalizes the memorized actions to adapt them to the present perception. This process creates a discrete lattice of continuous Sensory-Motor Contingencies that can control a robot in loco-manipulation tasks. Experiments on a 7-dof collaborative robotic arm with a gripper, and on a mobile manipulator demonstrate the functionality and versatility of the framework.
Full article
(This article belongs to the Section Sensors and Control in Robotics)
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Motion Planning of Differentially Flat Planar Underactuated Robots
by
Michele Tonan, Matteo Bottin, Alberto Doria and Giulio Rosati
Robotics 2024, 13(4), 57; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040057 - 30 Mar 2024
Abstract
Differential flat underactuated robots have fewer actuators than degrees of freedom (DOFs). This characteristic makes it possible to design light and cost-effective robots with great dexterity. The primary challenge associated with these robots lies in effectively controlling the passive joint, in particular, when
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Differential flat underactuated robots have fewer actuators than degrees of freedom (DOFs). This characteristic makes it possible to design light and cost-effective robots with great dexterity. The primary challenge associated with these robots lies in effectively controlling the passive joint, in particular, when collisions with obstacles in the workspace have to be avoided. Most of the previous research focused on point-to-point motions without any control on the actual robot trajectory. In this work, a new method is presented to plan trajectories that include one or more via points. In this way, the underactuated robot can avoid the obstacles in the workspace, similarly to traditional fully actuated robots. First, a trajectory planning strategy is analytically described; then, numerical results are presented. The numerical results show the effects of the via points and of the order of the polynomials adopted to define the motion laws. In addition, experimental tests performed on a two-DOF underactuated robot are presented, and their results validate the proposed method.
Full article
(This article belongs to the Special Issue Kinematics and Robot Design VI, KaRD2023)
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Posture Optimization of the TIAGo Highly-Redundant Robot for Grasping Operation
by
Albin Bajrami, Matteo-Claudio Palpacelli, Luca Carbonari and Daniele Costa
Robotics 2024, 13(4), 56; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040056 - 23 Mar 2024
Abstract
This study explores the optimization of the TIAGo robot’s configuration for grasping operation, with a focus on the context of aging. In fact, featuring a mobile base and a robotic arm, the TIAGo robot can conveniently aid individuals with disabilities, including those with
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This study explores the optimization of the TIAGo robot’s configuration for grasping operation, with a focus on the context of aging. In fact, featuring a mobile base and a robotic arm, the TIAGo robot can conveniently aid individuals with disabilities, including those with motor and cognitive impairments in both domestic and clinical settings. Its capabilities include recognizing visual targets such as faces or gestures using stereo cameras, as well as interpreting vocal commands through acoustic sensors to execute tasks. For example, the robot can grasp and lift objects such as a glass of water and navigate autonomously in order to fulfill a request. The paper presents the position and differential kinematics that form the basis for using the robot in numerous application contexts. In the present case, they are used to evaluate the kinematic performance of the robot relative to an assigned pose in the search for the optimal configuration with respect to the higher-order infinite possible configurations. Ultimately, the article provides insight into how to effectively use the robot in gripping operations, as well as presenting kinematic models of the TIAGo robot.
Full article
(This article belongs to the Special Issue Kinematics and Robot Design VI, KaRD2023)
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Practical Design Guidelines for Topology Optimization of Flexible Mechanisms: A Comparison between Weakly Coupled Methods
by
Simone D’Imperio, Teresa Maria Berruti, Chiara Gastaldi and Pietro Soccio
Robotics 2024, 13(4), 55; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13040055 - 23 Mar 2024
Abstract
Industrial robots are complex systems, as they require the integration of several sub-assemblies to perform accurate operations. Moreover, they may experience remarkable dynamic actions due to high kinematic requirements, which are necessary to obtain reduced cycle times. The dynamic design of industrial robots
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Industrial robots are complex systems, as they require the integration of several sub-assemblies to perform accurate operations. Moreover, they may experience remarkable dynamic actions due to high kinematic requirements, which are necessary to obtain reduced cycle times. The dynamic design of industrial robots can therefore be demanding, since the single structural component can induce an impact both in the design phase (development strategy and computational time) and at the machine level (global stiffness and natural frequencies). To this end, the present paper proposes first a topology optimization procedure based on the Equivalent Static Loads (ESL) method that integrates flexible multibody simulation outputs. The same procedure also foresees an intermediate static reduction to reduce and to precisely define the application points of the ESL. Secondly, an optimization procedure based on the Quasi-Static Loads (QSL) method integrating flexible multibody simulation outputs is proposed as well. The objective is to carry out a comparison between the two methods and consequently evaluate the benefits and drawbacks of the two. In the end, practical guidelines regarding the selection and application of the two methods are also provided to the reader.
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(This article belongs to the Section Industrial Robots and Automation)
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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030054 - 20 Mar 2024
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
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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.
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(This article belongs to the Special Issue Kinematics and Robot Design VI, KaRD2023)
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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
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
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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.
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(This article belongs to the Section AI in Robotics)
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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030052 - 16 Mar 2024
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
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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.
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(This article belongs to the Special Issue Intelligent Bionic Robots)
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Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation
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Alexandre Athayde, Alexandra Moutinho and José Raúl Azinheira
Robotics 2024, 13(3), 51; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030051 - 16 Mar 2024
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
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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.
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(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030050 - 15 Mar 2024
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
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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.
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(This article belongs to the Section Neurorobotics)
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Intelligent Robotics in Pediatric Cooperative Neurorehabilitation: A Review
by
Elishai Ezra Tsur and Odelia Elkana
Robotics 2024, 13(3), 49; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030049 - 14 Mar 2024
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
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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.
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(This article belongs to the Special Issue Neurorehabilitation Robotics: Recent Trends and Novel Applications)
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Trajectory Tracking and Disturbance Rejection Performance Analysis of Classical and Advanced Controllers for a SCORBOT Robot
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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
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
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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.
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(This article belongs to the Section Intelligent Robots and Mechatronics)
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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030047 - 11 Mar 2024
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
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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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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030046 - 08 Mar 2024
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
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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.
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(This article belongs to the Special Issue Autonomous Navigation of Mobile Robots in Unstructured Environments)
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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://0-doi-org.brum.beds.ac.uk/10.3390/robotics13030045 - 07 Mar 2024
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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.
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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.
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