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Robotics
Volume 14
Issue 10
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Robotics, Volume 14, Issue 10 (October 2025) – 17 articles

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23 pages, 3674 KB  
Article
Open-Access Simulation Platform and Motion Control Design for a Surface Robotic Vehicle in the VRX Environment
by Brayan Saldarriaga-Mesa, Julio Montesdeoca, Dennys Báez, Flavio Roberti and Juan Marcos Toibero
Robotics 2025, 14(10), 147; https://doi.org/10.3390/robotics14100147 - 21 Oct 2025
Viewed by 416
Abstract
This work presents an open-source simulation framework designed to extend the capabilities of the VRX environment for developing and validating control strategies for surface robotic vehicles. The platform features a custom monohull, kayak-type USV with four thrusters in differential configuration, represented with a [...] Read more.
This work presents an open-source simulation framework designed to extend the capabilities of the VRX environment for developing and validating control strategies for surface robotic vehicles. The platform features a custom monohull, kayak-type USV with four thrusters in differential configuration, represented with a complete graphical mockup consistent with its physical design and modeled with realistic dynamics and sensor integration. A thrust mapping function was calibrated using manufacturer data, and the vehicle’s behavior was characterized using a simplified Fossen model with parameters identified via Least Squares estimation. Multiple motion controllers, including velocity, position, trajectory tracking, and path guidance, were implemented and evaluated in a variety of wave and wind scenarios designed to test the full vehicle dynamics and closed-loop behavior. In addition to extending the VRX simulator, this work introduces a new USV model, a calibrated thrust response, and a set of model-based controllers validated in high-fidelity marine conditions. The resulting framework constitutes a reproducible and extensible resource for the marine robotics community, with direct applications in robotic education, perception, and advanced control systems. Full article
(This article belongs to the Section Sensors and Control in Robotics)
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43 pages, 8058 KB  
Article
Biomechanical Design and Adaptive Sliding Mode Control of a Human Lower Extremity Exoskeleton for Rehabilitation Applications
by Sk K. Hasan and Nafizul Alam
Robotics 2025, 14(10), 146; https://doi.org/10.3390/robotics14100146 - 21 Oct 2025
Viewed by 490
Abstract
The human lower extremity plays a vital role in locomotion, posture, and weight-bearing through coordinated motion at the hip, knee, and ankle joints. These joints facilitate essential functions including flexion, extension, and internal and external rotation. To address mobility impairments through personalized therapy, [...] Read more.
The human lower extremity plays a vital role in locomotion, posture, and weight-bearing through coordinated motion at the hip, knee, and ankle joints. These joints facilitate essential functions including flexion, extension, and internal and external rotation. To address mobility impairments through personalized therapy, this study presents the design, dynamic modeling, and control of a four-degree-of-freedom (4-DOF) lower limb exoskeleton robot. The system actuates hip flexion–extension and internal–external rotation, knee flexion–extension, and ankle dorsiflexion–plantarflexion. Anatomically aligned joint axes were incorporated to enhance biomechanical compatibility and reduce user discomfort. A detailed CAD model ensures ergonomic fit, modular adjustability, and the integration of actuators and sensors. The exoskeleton robot dynamic model, derived using Lagrangian mechanics, incorporates subject-specific anthropometric parameters to accurately reflect human biomechanics. A conventional sliding mode controller (SMC) was implemented to ensure robust trajectory tracking under model uncertainties. To overcome limitations of conventional SMC, an adaptive sliding mode controller with boundary layer-based chattering suppression was developed. Simulations in MATLAB/Simulink 2025 R2025a demonstrate that the adaptive controller achieves smoother torque profiles, minimizes high-frequency oscillations, and improves tracking accuracy. This work establishes a comprehensive framework for anatomically congruent exoskeleton design and robust control, supporting the future integration of physiological intent detection and clinical validation for neurorehabilitation applications. Full article
(This article belongs to the Section Neurorobotics)
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24 pages, 9665 KB  
Article
Achieving Accurate Turns with LEGO SPIKE Prime Robots
by Attila Körei, Szilvia Szilágyi and Ingrida Vaičiulyté
Robotics 2025, 14(10), 145; https://doi.org/10.3390/robotics14100145 - 17 Oct 2025
Cited by 1 | Viewed by 565
Abstract
LEGO SPIKE Prime robots (The LEGO Group, Billund, Denmark) are widely used in educational settings to foster STEM skills and develop problem-solving competencies. A common task in robotics classes and competitions is moving and controlling wheeled vehicles where precise manoeuvrability, especially turning, is [...] Read more.
LEGO SPIKE Prime robots (The LEGO Group, Billund, Denmark) are widely used in educational settings to foster STEM skills and develop problem-solving competencies. A common task in robotics classes and competitions is moving and controlling wheeled vehicles where precise manoeuvrability, especially turning, is essential for successful navigation. This study aims to provide a comprehensive analysis of the turning mechanisms of LEGO SPIKE Prime robots to facilitate more accurate and effective control. This research combines theoretical analysis with experimental validation. We mathematically derived formulas to relate wheel speeds and steering parameters to the turning radius, and we used regression analysis to refine our models. Additionally, we developed a method where the robot itself collects data on its turning performance, enabling autonomous regression modelling. We found that directly adjusting wheel speeds offers greater precision in turning than using a steering parameter. This finding is supported by the results of the Wilcoxon test, which was performed on a random sample of 30 elements and showed that the effect size is significant (r = 0.7) at a significance level of 0.05. This study provides educators and students with a detailed understanding of turning mechanisms and offers guidance on practical and effective means for achieving the accuracy and consistency needed in educational robotics and robot competitions. Full article
(This article belongs to the Section Educational Robotics)
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19 pages, 2092 KB  
Article
A Hybrid Control Scheme for Backdriving a Surgical Robot About a Pivot Point
by Mehmet İsmet Can Dede, Emir Mobedi and Mehmet Fırat Deniz
Robotics 2025, 14(10), 144; https://doi.org/10.3390/robotics14100144 - 16 Oct 2025
Viewed by 439
Abstract
An incision point acts as the pivot point when a minimally invasive surgery procedure is applied. The assistive robot arms employed for such operation must have the capability to perform a remote center of motion (RCM) at this pivot point. Other than designing [...] Read more.
An incision point acts as the pivot point when a minimally invasive surgery procedure is applied. The assistive robot arms employed for such operation must have the capability to perform a remote center of motion (RCM) at this pivot point. Other than designing RCM mechanisms, a common practice is to use a readily available spatial serial robot arm and control it to impose this RCM constraint. When this assistive robot is required to be backdriven by the surgeon, the relation between the interaction forces/moments and the motion with RCM constraint becomes challenging. This paper carefully formulates a hybrid position/force control scheme for this relationship when any readily available robot arm that is coupled with a force/torque sensor is used for an RCM task. The verification of the formulation is carried out on a readily available robot arm by implementing the additional constraints that are derived from a surgical robot application. Full article
(This article belongs to the Special Issue Selected Papers from MESROB2025: 9th IFToMM International Workshop on New Trends in Medical and Service Robotics)
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22 pages, 5278 KB  
Article
Modeling and Simulation of Lower Limb Rehabilitation Exoskeletons: A Comparative Analysis for Dynamic Model Validation and Optimal Approach Selection
by Rana Sami Ullah Khan, Muhammad Tallal Saeed, Zeashan Khan, Urooj Abid, Hafiz Zia Ur Rehman, Zareena Kausar and Shiyin Qin
Robotics 2025, 14(10), 143; https://doi.org/10.3390/robotics14100143 - 16 Oct 2025
Viewed by 490
Abstract
Accurate modeling and simulation of lower limb rehabilitation exoskeleton (LLRE) enables effective control resulting in enhanced performance and ensuring efficient rehabilitation. There are two primary objectives of this study. First is to validate the existing models and second is to identify the optimal [...] Read more.
Accurate modeling and simulation of lower limb rehabilitation exoskeleton (LLRE) enables effective control resulting in enhanced performance and ensuring efficient rehabilitation. There are two primary objectives of this study. First is to validate the existing models and second is to identify the optimal modeling approach for exoskeletons. For validation, firstly a lower limb rehabilitation exoskeleton is modeled using three different modeling approaches which include analytical modeling, bond graph modeling, and modeling through Simscape (SS). Thereafter, dynamic responses of analytical and graphical modeling are compared with SS model using key dynamic response parameters, including rise time, peak time, and others. The SS-based physical model can be employed for validation because SS, unlike mathematical modeling, uses unit-consistent physical domain data and, therefore, serves as an intermediate step between mathematical modeling and hardware validation. Secondly, to identify the most suitable modeling approach, a structured and comprehensive comparison of different modeling approaches based on aspects such as control domain, complexity, ease of use, and other relevant factors is carried out. The results highlight the qualitative strengths and limitations of the three approaches. Previous studies focus on individual methods and lack such comparison. This work contributes to the validation of models and identification of an efficient and effective modeling methodology for LLRE. The findings reveal that Simscape™ is the most suitable approach for modeling LLREs as it provides multidisciplinary system modeling and supports real-time simulation. The validated model can now be employed for advancements in model-based control design. Moreover, the identified optimal approach provides an insight to researchers and engineers for model selection in early-stage design and control development of complex mechatronic systems. Future work includes comparison of dynamic responses with actual hardware responses to experimentally validate the effectiveness of the model for real-world patient assistance and mobility restoration. Full article
(This article belongs to the Special Issue Development of Biomedical Robotics)
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2 pages, 139 KB  
Editorial
Special Issue “Legged Robots into the Real World, 2nd Edition”
by Chengxu Zhou
Robotics 2025, 14(10), 142; https://doi.org/10.3390/robotics14100142 - 13 Oct 2025
Viewed by 413
Abstract
Legged robots are widely recognised as one of the most ambitious frontiers in robotics, promising mobility and adaptability in environments where wheels and tracks cannot operate [...] Full article
(This article belongs to the Special Issue Legged Robots into the Real World, 2nd Edition)
32 pages, 5868 KB  
Review
A Review of Robotic Interfaces for Post-Stroke Upper-Limb Rehabilitation: Assistance Types, Actuation Methods, and Control Mechanisms
by André Gonçalves, Manuel F. Silva, Hélio Mendonça and Cláudia D. Rocha
Robotics 2025, 14(10), 141; https://doi.org/10.3390/robotics14100141 - 6 Oct 2025
Viewed by 850
Abstract
Stroke is a leading cause of long-term disability worldwide, with survivors often facing significant challenges in regaining upper-limb functionality. In response, robotic rehabilitation systems have emerged as promising tools to enhance post-stroke recovery by delivering precise, adaptable, and patient-specific therapy. This paper presents [...] Read more.
Stroke is a leading cause of long-term disability worldwide, with survivors often facing significant challenges in regaining upper-limb functionality. In response, robotic rehabilitation systems have emerged as promising tools to enhance post-stroke recovery by delivering precise, adaptable, and patient-specific therapy. This paper presents a review of robotic interfaces developed specifically for upper-limb rehabilitation. It analyses existing exoskeleton- and end-effector-based systems, with respect to three core design pillars: assistance types, control philosophies, and actuation methods. The review highlights that most solutions favor electrically actuated exoskeletons, which use impedance- or electromyography-driven control, with active assistance being the predominant rehabilitation mode. Resistance-providing systems remain underutilized. Furthermore, no hybrid approaches featuring the combination of robotic manipulators with actuated interfaces were found. This paper also identifies a recent trend towards lightweight, modular, and portable solutions and discusses the challenges in bridging research prototypes with clinical adoption. By focusing exclusively on upper-limb applications, this work provides a targeted reference for researchers and engineers developing next-generation rehabilitation technologies. Full article
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23 pages, 16253 KB  
Article
Preliminary Validation of Nitinol Rod Driven Discrete Continuum Robot for Transoral Surgery by Planar Path Planning with CT Images
by Yeoun-Jae Kim, Ji Eun Oh and Daehan Wi
Robotics 2025, 14(10), 140; https://doi.org/10.3390/robotics14100140 - 30 Sep 2025
Viewed by 465
Abstract
A Nitinol rod-driven discrete continuum robot with two sections and eight units was developed to support clinicians in performing transoral surgery. The robot measures 120 mm in length, with each unit having a diameter of 15 mm and a height of 20 mm. [...] Read more.
A Nitinol rod-driven discrete continuum robot with two sections and eight units was developed to support clinicians in performing transoral surgery. The robot measures 120 mm in length, with each unit having a diameter of 15 mm and a height of 20 mm. The distal and proximal sections are designed to bend independently, each with two degrees of freedom (DOF) actuated by four Nitinol rods. To validate the independent controllability of the two sections, two-dimensional bending tests and ANSYS simulations were conducted. For the assessment of clinical feasibility, head and neck CT images from ten patients were manually segmented to reconstruct three-dimensional oral cavity models. Ten fictitious reference passages were generated from the lips to the oropharynx, and planar path-planning simulations were performed using these passages. Verification experiments were carried out on three reference passages employing experimentally derived inverse kinematics. The simulation results demonstrated an average reference path-following error within a root mean square (RMS) of 1.9705 mm at maximum insertion length. Experimental path-planning results showed average absolute angular differences of 5.6 degrees in the distal section and 4.1 degrees in the proximal section when compared with the simulations. Full article
(This article belongs to the Special Issue Development of Biomedical Robotics)
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21 pages, 3122 KB  
Article
TGPSO: An Adaptive Gait Optimization Algorithm for Hexapod Robots in Multi-Terrain Environments
by Guiqiang Bai, Weixu Chen, Jingang Du, Yang Liu, Yanting Luo and Hongde Qin
Robotics 2025, 14(10), 139; https://doi.org/10.3390/robotics14100139 - 30 Sep 2025
Viewed by 555
Abstract
To address the limited adaptability of traditional fixed-parameter strategies for hexapod robots operating in multi-material terrain environments, this study proposes a terrain-aware gait optimization method based on an improved particle swarm optimization algorithm that incorporates foot-end sinking perception. This method establishes a ground [...] Read more.
To address the limited adaptability of traditional fixed-parameter strategies for hexapod robots operating in multi-material terrain environments, this study proposes a terrain-aware gait optimization method based on an improved particle swarm optimization algorithm that incorporates foot-end sinking perception. This method establishes a ground sinking detection mechanism based on foot-end position sensors, constructs a dynamic weight allocation strategy based on ground bearing capacity, and develops a Terrain-aware Ground Particle Swarm Optimization algorithm (TGPSO) that integrates Latin hypercube sampling, linearly decreasing inertia weights, and stagnation exploration mechanisms. Furthermore, it establishes a unified terrain-based reward function framework to achieve dynamic adjustment of weights for velocity, stability, and transportation efficiency. Simulink simulation verification demonstrates that TGPSO achieves superior optimization performance compared to traditional strategies across three typical terrain types, while exhibiting faster convergence speed and enhanced stability. The research findings provide theoretical foundations and technical support for intelligent motion control of hexapod robots across varying material properties, achieving targeted optimization of locomotion performance under diverse terrain conditions. Full article
(This article belongs to the Section AI in Robotics)
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16 pages, 4945 KB  
Article
Research on Energy Consumption Optimization Strategies of Robot Joints Based on NSGA-II and Energy Consumption Mapping
by Dong Yang, Xin Wei and Ming Han
Robotics 2025, 14(10), 138; https://doi.org/10.3390/robotics14100138 - 29 Sep 2025
Viewed by 516
Abstract
Robot energy consumption is a prominent challenge in intelligent manufacturing and construction. Reducing energy consumption during robot trajectory execution is an urgent issue requiring immediate attention. In view of the shortcomings of traditional trajectory optimization methods, this paper proposes a multi-objective trajectory optimization [...] Read more.
Robot energy consumption is a prominent challenge in intelligent manufacturing and construction. Reducing energy consumption during robot trajectory execution is an urgent issue requiring immediate attention. In view of the shortcomings of traditional trajectory optimization methods, this paper proposes a multi-objective trajectory optimization method that combines energy consumption mapping with the NSGA-II, aiming to reduce robots’ trajectory energy consumption and optimize execution efficiency. By establishing a dynamic energy consumption model, energy consumption mapping is employed to constrain energy consumption within the robot’s workspace, thereby providing guidance for the optimization process. Simultaneously, with energy consumption minimization and time consumption as optimization objectives, the NSGA-II is utilized to obtain the Pareto-optimal solution set through non-dominated sorting and congestion distance calculation. Energy consumption mapping serves as a dynamic feedback mechanism during the optimization process, guiding the distribution of trajectory points towards low-energy-consumption regions, accelerating algorithm convergence, and enhancing the quality of the solution set. The experimental results demonstrate that the proposed method can significantly reduce robots’ trajectory energy consumption and achieve an effective balance between energy consumption and time consumption. Compared with the conventional NSGA-II normalized weighted function method in similar task scenarios, the robot can save 14.87% and 10.47% of its energy consumption, respectively. Compared with traditional methods, this method exhibits superior energy-saving performance and adaptability in complex task environments, providing a novel solution for the efficient trajectory planning of robots. Full article
(This article belongs to the Section Industrial Robots and Automation)
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17 pages, 26449 KB  
Article
Federated Learning for Distributed Multi-Robotic Arm Trajectory Optimization
by Fazal Khan and Zhuo Meng
Robotics 2025, 14(10), 137; https://doi.org/10.3390/robotics14100137 - 29 Sep 2025
Viewed by 620
Abstract
The optimization of trajectories for multiple robotic arms in a shared workspace is critical for industrial automation but presents significant challenges, including data sharing, communication overhead, and adaptability in dynamic environments. Traditional centralized control methods require sharing raw sensor data, raising concerns and [...] Read more.
The optimization of trajectories for multiple robotic arms in a shared workspace is critical for industrial automation but presents significant challenges, including data sharing, communication overhead, and adaptability in dynamic environments. Traditional centralized control methods require sharing raw sensor data, raising concerns and creating computational bottlenecks. This paper proposes a novel Federated Learning (FL) framework for distributed multi-robotic arm trajectory optimization. Our method enables collaborative learning where robots train a shared model locally and only exchange gradient updates, preserving data privacy. The framework integrates an adaptive Rapidly exploring Random Tree (RRT) algorithm enhanced with a dynamic pruning strategy to reduce computational overhead and ensure collision-free paths. Real-time synchronization is achieved via EtherCAT, ensuring precise coordination. Experimental results demonstrate that our approach achieves a 17% reduction in average path length, a 22% decrease in collision rate, and a 31% improvement in planning speed compared to a centralized RRT baseline, while reducing inter-robot communication overhead by 45%. This work provides a scalable and efficient solution for collaborative manipulation in applications ranging from assembly lines to warehouse automation. Full article
(This article belongs to the Section Sensors and Control in Robotics)
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24 pages, 1542 KB  
Article
Investigating Learning Assistance by Demonstration for Robotic Wheelchairs: A Simulation Approach
by Vinícius Barbosa Schettino, Murillo Ferreira dos Santos and Paolo Mercorelli
Robotics 2025, 14(10), 136; https://doi.org/10.3390/robotics14100136 - 28 Sep 2025
Viewed by 373
Abstract
A major challenge for robots that provide physical assistance is adapting to the needs of different people. To overcome this, personalised assistive models can be created by observing the demonstrations of help provided by an assistant, a setting known as Learning Assistance by [...] Read more.
A major challenge for robots that provide physical assistance is adapting to the needs of different people. To overcome this, personalised assistive models can be created by observing the demonstrations of help provided by an assistant, a setting known as Learning Assistance by Demonstration (LAD). In this work, the case of robotic wheelchairs and drivers with hand control disabilities, which make navigation more challenging, was considered. To better understand LAD and its features, a simulator capable of generating repeatable examples of the triadic interactions between drivers, robots, and assistants was developed. The software is designed to be modular and parametrisable, enabling customisation and experimentation with various synthetic disabilities and scenarios. This approach was employed to design more effective data collection procedures and to enhance learning models. With these, it is shown that, at least in simulation, LAD can be used as follows: for different disabilities; to help consistently; to generalise to physically different environments; and to create customised assistive policies. In summary, the results provide further evidence that LAD is a viable approach for efficiently creating personalised assistive solutions for robotic wheelchairs. Full article
(This article belongs to the Section Intelligent Robots and Mechatronics)
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21 pages, 27803 KB  
Article
Improving Rover Path Planning in Challenging Terrains: A Comparative Study of RRT-Based Algorithms
by Sarah Swinton, Euan McGookin and Douglas Thomson
Robotics 2025, 14(10), 135; https://doi.org/10.3390/robotics14100135 - 26 Sep 2025
Viewed by 523
Abstract
Autonomous planetary rovers require robust path planning over rough 3D terrains, where traditional metrics such as path length, number of nodes, and planning time do not adequately capture path quality. Rapidly Exploring Random Trees (RRT) and its asymptotically optimal variant, RRT*, are widely [...] Read more.
Autonomous planetary rovers require robust path planning over rough 3D terrains, where traditional metrics such as path length, number of nodes, and planning time do not adequately capture path quality. Rapidly Exploring Random Trees (RRT) and its asymptotically optimal variant, RRT*, are widely used sampling-based algorithms for non-holonomic mobile robots but are limited when traversing uneven 3D terrain. This study proposes 3D-RRT*, a simplified, terrain-aware extension of Traversability-Based RRT*, designed to maintain high path quality while reducing planning time. The performance of 3D-RRT* is evaluated using metrics that are both practical and meaningful in the context of planetary rover path planning: path smoothness, path flatness, path length, and planning time. Exploration of a simulated Martian surface demonstrates that 3D-RRT* significantly improves path quality compared to standard RRT and RRT*, achieving smoother, safer, and more efficient routes for planetary rover missions. Full article
(This article belongs to the Section Aerospace Robotics and Autonomous Systems)
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28 pages, 10315 KB  
Article
DKB-SLAM: Dynamic RGB-D Visual SLAM with Efficient Keyframe Selection and Local Bundle Adjustment
by Qian Sun, Ziqiang Xu, Yibing Li, Yidan Zhang and Fang Ye
Robotics 2025, 14(10), 134; https://doi.org/10.3390/robotics14100134 - 25 Sep 2025
Viewed by 952
Abstract
Reliable navigation for mobile robots in dynamic, human-populated environments remains a significant challenge, as moving objects often cause localization drift and map corruption. While Simultaneous Localization and Mapping (SLAM) techniques excel in static settings, issues like keyframe redundancy and optimization inefficiencies further hinder [...] Read more.
Reliable navigation for mobile robots in dynamic, human-populated environments remains a significant challenge, as moving objects often cause localization drift and map corruption. While Simultaneous Localization and Mapping (SLAM) techniques excel in static settings, issues like keyframe redundancy and optimization inefficiencies further hinder their practical deployment on robotic platforms. To address these challenges, we propose DKB-SLAM, a real-time RGB-D visual SLAM system specifically designed to enhance robotic autonomy in complex dynamic scenes. DKB-SLAM integrates optical flow with Gaussian-based depth distribution analysis within YOLO detection frames to efficiently filter dynamic points, crucial for maintaining accurate pose estimates for the robot. An adaptive keyframe selection strategy balances map density and information integrity using a sliding window, considering the robot’s motion dynamics through parallax, visibility, and matching quality. Furthermore, a heterogeneously weighted local bundle adjustment (BA) method leverages map point geometry, assigning higher weights to stable edge points to refine the robot’s trajectory. Evaluations on the TUM RGB-D benchmark and, crucially, on a mobile robot platform in real-world dynamic scenarios, demonstrate that DKB-SLAM outperforms state-of-the-art methods, providing a robust and efficient solution for high-precision robot localization and mapping in dynamic environments. Full article
(This article belongs to the Special Issue SLAM and Adaptive Navigation for Robotics)
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18 pages, 10386 KB  
Article
Mixed-Reality (MR) Enhanced Human–Robot Collaboration: Communicating Robot Intentions to Humans
by Kaiyuan Zhang, Yuchen Yan and Yunyi Jia
Robotics 2025, 14(10), 133; https://doi.org/10.3390/robotics14100133 - 24 Sep 2025
Viewed by 891
Abstract
Advancements in collaborative robotics have significantly enhanced the potential for human–robot collaboration in manufacturing. To achieve efficient and user-friendly collaboration, prior research has predominantly focused on the robot’s perspective, including aspects such as planning, control, and adaptation. A key approach in this domain [...] Read more.
Advancements in collaborative robotics have significantly enhanced the potential for human–robot collaboration in manufacturing. To achieve efficient and user-friendly collaboration, prior research has predominantly focused on the robot’s perspective, including aspects such as planning, control, and adaptation. A key approach in this domain has been the recognition of human intentions to inform robot actions. However, true collaboration necessitates bidirectional communication, where both human and robot are aware of each other’s intentions. A lack of transparency in robot actions can lead to discomfort, reduced safety, and inefficiencies in the collaborative process. This study investigates the communication of robot intentions to human operators through mixed reality (MR) and evaluates its impact on human–robot collaboration. A laboratory-based physical human–robot assembly framework is developed, integrating multiple MR-based intention communication strategies. Experimental evaluations are conducted to assess the effectiveness of these strategies. The results demonstrate that conveying robot intentions via MR enhances work efficiency, trust, and user comfort in human–robot collaborative manufacturing. Furthermore, a comparative analysis of different MR-based communication designs provides insights into the optimal approaches for improving collaboration quality. Full article
(This article belongs to the Section Humanoid and Human Robotics)
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31 pages, 3516 KB  
Review
Design, Control, and Applications of Granular Jamming Grippers in Soft Robotics
by J. Cortes and C. Miranda
Robotics 2025, 14(10), 132; https://doi.org/10.3390/robotics14100132 - 24 Sep 2025
Viewed by 1602
Abstract
Granular jamming grippers have emerged as a versatile solution in soft robotics due to their ability to manipulate objects of various shapes and sizes, earning them the label of “universal grippers”. They are composed of granular material confined within an elastic membrane that [...] Read more.
Granular jamming grippers have emerged as a versatile solution in soft robotics due to their ability to manipulate objects of various shapes and sizes, earning them the label of “universal grippers”. They are composed of granular material confined within an elastic membrane that conforms to the object like a fluid and solidifies upon vacuum application, enabling a firm grip through friction and grain interlocking. This work provides a systematic review of the state of the art, addressing their physical principles, the influence of grain and membrane properties, performance characterization methods, and applications across diverse fields. Additionally, the main control variables of these grippers closely related to state variables used in control systems are discussed, along with the current knowledge gaps. Finally, five potential directions for future research are proposed. Full article
(This article belongs to the Special Issue Dynamic Modeling and Model-Based Control of Soft Robots)
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15 pages, 21804 KB  
Article
Automated On-Tree Detection and Size Estimation of Pomegranates by a Farmer Robot
by Rosa Pia Devanna, Francesco Vicino, Simone Pietro Garofalo, Gaetano Alessandro Vivaldi, Simone Pascuzzi, Giulio Reina and Annalisa Milella
Robotics 2025, 14(10), 131; https://doi.org/10.3390/robotics14100131 - 23 Sep 2025
Viewed by 588
Abstract
Pomegranate (Punica granatum) fruit size estimation plays a crucial role in orchard management decision-making, especially for fruit quality assessment and yield prediction. Currently, fruit sizing for pomegranates is performed manually using calipers to measure equatorial and polar diameters. These methods rely [...] Read more.
Pomegranate (Punica granatum) fruit size estimation plays a crucial role in orchard management decision-making, especially for fruit quality assessment and yield prediction. Currently, fruit sizing for pomegranates is performed manually using calipers to measure equatorial and polar diameters. These methods rely on human judgment for sample selection, they are labor-intensive, and prone to errors. In this work, a novel framework for automated on-tree detection and sizing of pomegranate fruits by a farmer robot equipped with a consumer-grade RGB-D sensing device is presented. The proposed system features a multi-stage transfer learning approach to segment fruits in RGB images. Segmentation results from each image are projected on the co-located depth image; then, a fruit clustering and modeling algorithm using visual and depth information is implemented for fruit size estimation. Field tests carried out in a commercial orchard are presented for 96 pomegranate fruit samples, showing that the proposed approach allows for accurate fruit size estimation with an average discrepancy with respect to caliper measures of about 1.0 cm on both the polar and equatorial diameter. Full article
(This article belongs to the Section Agricultural and Field Robotics)
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