Robotics

17 pages, 6269 KB

Open AccessArticle

Robust Graph-Based Spatial Coupling of Dynamic Movement Primitives for Multi-Robot Manipulation

by Zhenxi Cui, Jiacong Chen, Xin Xu and Henry K. Chu

Robotics 2026, 15(1), 29; https://doi.org/10.3390/robotics15010029 - 22 Jan 2026

Viewed by 107

Dynamic Movement Primitives (DMPs) provide a flexible framework for robotic trajectory generation, offering adaptability, robustness to disturbances, and modulation of predefined motions. Yet achieving reliable spatial coupling among multiple DMPs in cooperative manipulation tasks remains a challenge. This paper introduces a graph-based trajectory [...] Read more.

Dynamic Movement Primitives (DMPs) provide a flexible framework for robotic trajectory generation, offering adaptability, robustness to disturbances, and modulation of predefined motions. Yet achieving reliable spatial coupling among multiple DMPs in cooperative manipulation tasks remains a challenge. This paper introduces a graph-based trajectory planning framework that designs dynamic controllers to couple multiple DMPs while preserving formation. The proposed method is validated in both simulation and real-world experiments on a dual-arm UR5 robot performing tasks such as soft cloth folding and object transportation. Results show faster convergence and improved noise resilience compared to conventional approaches. These findings demonstrate the potential of the proposed framework for rapid deployment and effective trajectory planning in multi-robot manipulation. Full article

(This article belongs to the Special Issue Visual Servoing-Based Robotic Manipulation)

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25 pages, 1674 KB

Open AccessArticle

Relaxed Monotonic QMIX (R-QMIX): A Regularized Value Factorization Approach to Decentralized Multi-Agent Reinforcement Learning

by Liam O’Brien and Hao Xu

Robotics 2026, 15(1), 28; https://doi.org/10.3390/robotics15010028 - 21 Jan 2026

Viewed by 150

Abstract

Value factorization methods have become a standard tool for cooperative multi-agent reinforcement learning (MARL) in the centralized-training, decentralized-execution (CTDE) setting. QMIX (a monotonic mixing network for value factorization), in particular, constrains the joint action–value function to be a monotonic mixing of per-agent utilities, [...] Read more.

Value factorization methods have become a standard tool for cooperative multi-agent reinforcement learning (MARL) in the centralized-training, decentralized-execution (CTDE) setting. QMIX (a monotonic mixing network for value factorization), in particular, constrains the joint action–value function to be a monotonic mixing of per-agent utilities, which guarantees consistency with individual greedy policies but can severely limit expressiveness on tasks with non-monotonic agent interactions. This work revisits this design choice and proposes Relaxed Monotonic QMIX (R-QMIX), a simple regularized variant of QMIX that encourages but does not strictly enforce the monotonicity constraint. R-QMIX removes the sign constraints on the mixing network weights and introduces a differentiable penalty on negative partial derivatives of the joint value with respect to each agent’s utility. This preserves the computational benefits of value factorization while allowing the joint value to deviate from strict monotonicity when beneficial. R-QMIX is implemented in a standard PyMARL (an open-source MARL codebase) and evaluated on the StarCraft Multi-Agent Challenge (SMAC). On a simple map (3m), R-QMIX matches the asymptotic performance of QMIX while learning substantially faster. On more challenging maps (MMM2, 6h vs. 8z, and 27m vs. 30m), R-QMIX significantly improves both sample efficiency and final win rate (WR), for example increasing the final-quarter mean win rate from

42.3 %

to

97.1 %

on MMM2, from

0.0 %

to

57.5 %

on 6h vs. 8z, and from

58.0 %

to

96.6 %

on 27m vs. 30m. These results suggest that soft monotonicity regularization is a practical way to bridge the gap between strictly monotonic value factorization and fully unconstrained joint value functions. A further comparison against QTRAN (Q-value transformation), a more expressive value factorization method, shows that R-QMIX achieves higher and more reliably convergent win rates on the challenging SMAC maps considered. Full article

(This article belongs to the Special Issue AI-Powered Robotic Systems: Learning, Perception and Decision-Making)

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14 pages, 1255 KB

Open AccessArticle

Real-Time Control of Six-DOF Serial Manipulators via Learned Spherical Kinematics

by Meher Madhu Dharmana and Pramod Sreedharan

Robotics 2026, 15(1), 27; https://doi.org/10.3390/robotics15010027 - 21 Jan 2026

Viewed by 136

Abstract

Achieving reliable and real-time inverse kinematics (IK) for 6-degree-of-freedom (6-DoF) spherical-wrist manipulators remains a significant challenge. Analytical formulations often struggle with complex geometries and modeling errors, and standard numerical solvers (e.g., Levenberg–Marquardt) can stall near singularities or converge slowly. Purely data-driven approaches may [...] Read more.

Achieving reliable and real-time inverse kinematics (IK) for 6-degree-of-freedom (6-DoF) spherical-wrist manipulators remains a significant challenge. Analytical formulations often struggle with complex geometries and modeling errors, and standard numerical solvers (e.g., Levenberg–Marquardt) can stall near singularities or converge slowly. Purely data-driven approaches may require large networks and struggle with extrapolation. In this paper, we propose a low-latency, polynomial-based IK solution for spherical-wrist robots. The method leverages spherical coordinates and low-degree polynomial fits for the first three (positional) joints, coupled with a closed-form analytical solver for the final three (wrist) joints. An iterative partial-derivative refinement adjusts the polynomial-based angle estimates using spherical-coordinate errors, ensuring near-zero final error without requiring a full Jacobian matrix. The method systematically enumerates up to eight valid IK solutions per target pose. Our experiments against Levenberg–Marquardt, damped least-squares, and an fmincon baseline show an approximate 8.1× speedup over fmincon while retaining higher accuracy and multi-branch coverage. Future extensions include enhancing robustness through uncertainty propagation, adapting the approach to non-spherical wrists, and developing criteria-based automatic solution-branch selection. Full article

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

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4 pages, 139 KB

Open AccessEditorial

UAV Systems and Swarm Robotics

by Gerardo Flores, Héctor M. Becerra, Juan Pablo Ramirez-Paredes and Alexandre Santos Brandão

Robotics 2026, 15(1), 26; https://doi.org/10.3390/robotics15010026 - 20 Jan 2026

Viewed by 199

Abstract

A possible classification for organization purposes: [...] Full article

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

20 pages, 1970 KB

Open AccessReview

Synergistic Advancement of Physical and Information Interaction in Exoskeleton Rehabilitation Robotics: A Review

by Cuizhi Fei, Qiaoling Meng, Hongliu Yu and Xuhua Lu

Robotics 2026, 15(1), 25; https://doi.org/10.3390/robotics15010025 - 19 Jan 2026

Viewed by 222

Abstract

The exoskeleton rehabilitation robot is a structural robot that uses the actuator to control, so as to construct a human–robot collaborative rehabilitation training system to realize the perception and decoding of patients and promotes the recovery of limb function and neural remodeling. This [...] Read more.

The exoskeleton rehabilitation robot is a structural robot that uses the actuator to control, so as to construct a human–robot collaborative rehabilitation training system to realize the perception and decoding of patients and promotes the recovery of limb function and neural remodeling. This review focused on the synergistic advancement of physical and information interaction in exoskeleton rehabilitation robotics. This review systematically retrieved literature related to the synergistic advancement of physical and information interaction in exoskeleton rehabilitation robotics. Publications from 2011 to 2025 were searched for across the EI, IEEE Xplore, PubMed, and Web of Science databases. The included studies mainly covered the period from 2018 to 2025, reflecting recent technological progress. This article summarizes the collaborative progress of physical and informational interaction in exoskeleton rehabilitation robots. The physical and information interaction is manifested in the bionic structure, physiological information detection and information processing technology to identify human movement intention. The bionic structural design is fundamental to realize natural coordination between human and robot to improve the following of movements. The active participation and movement intention recognition accuracy are enhanced based on multimodal physiological signal detection and information processing technology, which provides a clear direction for the development of intelligent rehabilitation technology. Full article

(This article belongs to the Section Neurorobotics)

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27 pages, 4407 KB

Open AccessSystematic Review

Artificial Intelligence in Agri-Robotics: A Systematic Review of Trends and Emerging Directions Leveraging Bibliometric Tools

by Simona Casini, Pietro Ducange, Francesco Marcelloni and Lorenzo Pollini

Robotics 2026, 15(1), 24; https://doi.org/10.3390/robotics15010024 - 15 Jan 2026

Viewed by 391

Abstract

Agricultural robotics and artificial intelligence (AI) are becoming essential to building more sustainable, efficient, and resilient food systems. As climate change, food security pressures, and labour shortages intensify, the integration of intelligent technologies in agriculture has gained strategic importance. This systematic review provides [...] Read more.

Agricultural robotics and artificial intelligence (AI) are becoming essential to building more sustainable, efficient, and resilient food systems. As climate change, food security pressures, and labour shortages intensify, the integration of intelligent technologies in agriculture has gained strategic importance. This systematic review provides a consolidated assessment of AI and robotics research in agriculture from 2000 to 2025, identifying major trends, methodological trajectories, and underexplored domains. A structured search was conducted in the Scopus database—which was selected for its broad coverage of engineering, computer science, and agricultural technology—and records were screened using predefined inclusion and exclusion criteria across title, abstract, keywords, and eligibility levels. The final dataset was analysed through descriptive statistics and science-mapping techniques (VOSviewer, SciMAT). Out of 4894 retrieved records, 3673 studies met the eligibility criteria and were included. As with all bibliometric reviews, the synthesis reflects the scope of indexed publications and available metadata, and potential selection bias was mitigated through a multi-stage screening workflow. The analysis revealed four dominant research themes: deep-learning-based perception, UAV-enabled remote sensing, data-driven decision systems, and precision agriculture. Several strategically relevant but underdeveloped areas also emerged, including soft manipulation, multimodal sensing, sim-to-real transfer, and adaptive autonomy. Geographical patterns highlight a strong concentration of research in China and India, reflecting agricultural scale and investment dynamics. Overall, the field appears technologically mature in perception and aerial sensing but remains limited in physical interaction, uncertainty-aware control, and long-term autonomous operation. These gaps indicate concrete opportunities for advancing next-generation AI-driven robotic systems in agriculture. Funding sources are reported in the full manuscript. Full article

(This article belongs to the Special Issue Smart Agriculture with AI and Robotics)

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60 pages, 3790 KB

Open AccessReview

Autonomous Mobile Robot Path Planning Techniques—A Review: Metaheuristic and Cognitive Techniques

by Mubarak Badamasi Aremu, Gamil Ahmed, Sami Elferik and Abdul-Wahid A. Saif

Robotics 2026, 15(1), 23; https://doi.org/10.3390/robotics15010023 - 14 Jan 2026

Viewed by 414

Abstract

Autonomous mobile robots (AMRs) require robust, efficient path planning to operate safely in complex, often dynamic environments (e.g., logistics, transportation, and healthcare). This systematic review focuses on advanced metaheuristic and learning- and reasoning-based (cognitive) techniques for AMR path planning. Drawing on approximately 230 [...] Read more.

Autonomous mobile robots (AMRs) require robust, efficient path planning to operate safely in complex, often dynamic environments (e.g., logistics, transportation, and healthcare). This systematic review focuses on advanced metaheuristic and learning- and reasoning-based (cognitive) techniques for AMR path planning. Drawing on approximately 230 articles published between 2018 and 2025, we organize the literature into two prominent families, metaheuristic optimization and AI-based navigation, and introduce and apply a unified taxonomy (planning scope, output type, and constraint awareness) to guide the comparative analysis and practitioner-oriented synthesis. We synthesize representative approaches, including swarm- and evolutionary-based planners (e.g., PSO, GA, ACO, GWO), fuzzy and neuro-fuzzy systems, neural methods, and RL/DRL-based navigation, highlighting their operating principles, recent enhancements, strengths, and limitations, and typical deployment roles within hierarchical navigation stacks. Comparative tables and a compact trade-off synthesis summarize capabilities across static/dynamic settings, real-world validation, and hybridization trends. Persistent gaps remain in parameter tuning, safety, and interpretability of learning-enabled navigation; sim-to-real transfer; scalability under real-time compute limits; and limited physical experimentation. Finally, we outline research opportunities and open research questions, covering benchmarking and reproducibility, resource-aware planning, multi-robot coordination, 3D navigation, and emerging foundation models (LLMs/VLMs) for high-level semantic navigation. Collectively, this review provides a consolidated reference and practical guidance for future AMR path-planning research. Full article

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

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25 pages, 4540 KB

Open AccessArticle

Vision-Guided Grasp Planning for Prosthetic Hands with AABB-Based Object Representation

by Shifa Sulaiman, Akash Bachhar, Ming Shen and Simon Bøgh

Robotics 2026, 15(1), 22; https://doi.org/10.3390/robotics15010022 - 14 Jan 2026

Viewed by 229

Abstract

Recent advancements in prosthetic technology have increasingly focused on enhancing dexterity and autonomy through intelligent control systems. Vision-based approaches offer promising results for enabling prosthetic hands to interact more naturally with diverse objects in dynamic environments. Building on this foundation, the paper presents [...] Read more.

Recent advancements in prosthetic technology have increasingly focused on enhancing dexterity and autonomy through intelligent control systems. Vision-based approaches offer promising results for enabling prosthetic hands to interact more naturally with diverse objects in dynamic environments. Building on this foundation, the paper presents a vision-guided grasping algorithm for a prosthetic hand, integrating perception, planning, and control for dexterous manipulation. A camera mounted on the set up captures the scene, and a Bounding Volume Hierarchy (BVH)-based vision algorithm is employed to segment an object for grasping and define its bounding box. Grasp contact points are then computed by generating candidate trajectories using Rapidly-exploring Random Tree Star (RRT*) algorithm, and selecting fingertip end poses based on the minimum Euclidean distance between these trajectories and the object’s point cloud. Each finger’s grasp pose is determined independently, enabling adaptive, object-specific configurations. Damped Least Square (DLS) based Inverse kinematics solver is used to compute the corresponding joint angles, which are subsequently transmitted to the finger actuators for execution. Our intention in this work was to present a proof-of-concept pipeline demonstrating that fingertip poses derived from a simple, computationally lightweight geometric representation, specifically an AABB-based segmentation can be successfully propagated through per-finger planning and executed in real time on the Linker Hand O7 platform. The proposed method is validated in simulation, and experimental integration on a Linker Hand O7 platform. Full article

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

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23 pages, 4679 KB

Open AccessArticle

A Synergistic Rehabilitation Approach for Post-Stroke Patients with a Hand Exoskeleton: A Feasibility Study with Healthy Subjects

by Cristian Camardella, Tommaso Bagneschi, Federica Serra, Claudio Loconsole and Antonio Frisoli

Robotics 2026, 15(1), 21; https://doi.org/10.3390/robotics15010021 - 14 Jan 2026

Viewed by 256

Abstract

Hand exoskeletons are increasingly used to support post-stroke reach-to-grasp, yet most intention-detection strategies trigger assistance from local hand events without considering the synergy between proximal arm transport and distal hand shaping. We evaluated whether proximal arm kinematics, alone or fused with EMG, can [...] Read more.

Hand exoskeletons are increasingly used to support post-stroke reach-to-grasp, yet most intention-detection strategies trigger assistance from local hand events without considering the synergy between proximal arm transport and distal hand shaping. We evaluated whether proximal arm kinematics, alone or fused with EMG, can predict flexor and extensor digitorum activity for synergy-aligned hand assistance. We trained nine models per participant: linear regression (LINEAR), feedforward neural network (NONLINEAR), and LSTM, each under EMG-only, kinematics-only (KIN), and EMG+KIN inputs. Performance was assessed by RMSE on test trials and by a synergy-retention analysis, comparing synergy weights from original EMG versus a hybrid EMG in which extensor and flexor digitorum measure signals were replaced by model predictions. Results have shown that kinematic information can predict muscle activity even with a simple linear model (average RMSE around 30% of signal amplitude peak during go-to-grasp contractions), and synergy analysis indicated high cosine similarity between original and hybrid synergy weights (on average 0.87 for the LINEAR model). Furthermore, the LINEAR model with kinematics input has been tested in a real-time go-to-grasp motion, developing a high-level control strategy for a hand exoskeleton, to better simulate post-stroke rehabilitation scenarios. These results suggest the intrinsic synergistic motion of go-to-grasp actions, offering a practical path, in hand rehabilitation contexts, for timing hand assistance in synergy with arm transport and with minimal setup burden. Full article

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

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44 pages, 5363 KB

Open AccessReview

End-Effector-Based Robots for Post-Stroke Rehabilitation of Proximal Arm Joints: A Literature Review

by Sohrab Moayer, Redwan Alqasemi and Rajiv Dubey

Robotics 2026, 15(1), 20; https://doi.org/10.3390/robotics15010020 - 13 Jan 2026

Viewed by 421

Abstract

Experiencing weakness or paralysis on one side of the body is a common consequence of stroke, with approximately 8 out of 10 patients experiencing some degree of Hemiparesis. Rehabilitation through physiotherapy and occupational therapy is one of the primary methods used to alleviate [...] Read more.

Experiencing weakness or paralysis on one side of the body is a common consequence of stroke, with approximately 8 out of 10 patients experiencing some degree of Hemiparesis. Rehabilitation through physiotherapy and occupational therapy is one of the primary methods used to alleviate these conditions. However, physiotherapy, provided by a therapist, is not always readily available. Rehabilitation robots have been studied as alternatives and supplements to conventional therapy. These robots, based on their interaction with the user, can be categorized as end-effector and exoskeleton-based robots. This work aims to examine end-effector rehabilitation robots targeting hemiplegic arm’s proximal joints (shoulder and elbow) for post-stroke recovery. Additionally, we analyze their mechanical design, training modes, user interfaces, and clinical outcomes, highlighting trends and gaps in these systems. Furthermore, we suggest design considerations for home-based therapy and future integration with tele-rehabilitation, based on our findings. This review uniquely focuses on end-effector robots for proximal joints, synthesizing design trends and clinical evidence to guide future development. Full article

(This article belongs to the Special Issue Development of Biomedical Robotics)

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38 pages, 5190 KB

Open AccessArticle

Discrete-Time Computed Torque Control with PSO-Based Tuning for Energy-Efficient Mobile Manipulator Trajectory Tracking

by Patricio Galarce-Acevedo and Miguel Torres-Torriti

Robotics 2026, 15(1), 19; https://doi.org/10.3390/robotics15010019 - 9 Jan 2026

Viewed by 268

Abstract

Mobile manipulator robots have an increasing number of applications in industry because they extend the workspace of a fixed base manipulator mounted on a mobile platform, making it important to further investigate their control and optimization. This paper presents an implementation proposal for [...] Read more.

Mobile manipulator robots have an increasing number of applications in industry because they extend the workspace of a fixed base manipulator mounted on a mobile platform, making it important to further investigate their control and optimization. This paper presents an implementation proposal for a coupled base–arm dynamics computed torque controller (CTC) for trajectory tracking of a differential-drive mobile manipulator, which considers the dynamics of the fixed base manipulator and the mobile base in a coupled way and compares its performance with that of a Proportional Derivative (PD) controller. Both controllers are tuned using Particle Swarm Optimization (PSO) with a cost function that aims to simultaneously reduce the control energy and the end-effector tracking error for different types of trajectories, and they operate in discrete time, thus accounting for inherent process delays. Simulation and laboratory implementation results show the superior performance of the CTC in both cases: in simulation, the average end-effector positioning error is reduced by 51.55% and the average RMS power by 46.44%; in the laboratory experiments, the average end-effector positioning error is reduced by 43.29% and the average RMS power by 53.49%, even in the presence of possible model uncertainties and system disturbances. Full article

(This article belongs to the Special Issue Motion Planning for Autonomous and Intelligent Mobile Robots in Unstructured Environments)

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Graphical abstract

23 pages, 15741 KB

Open AccessArticle

A Hierarchical Trajectory Planning Framework for Autonomous Underwater Vehicles via Spatial–Temporal Alternating Optimization

by Jinjin Yan and Huiling Zhang

Robotics 2026, 15(1), 18; https://doi.org/10.3390/robotics15010018 - 9 Jan 2026

Viewed by 219

Abstract

Autonomous underwater vehicle (AUV) motion planning in complex three-dimensional ocean environments remains challenging due to the simultaneous requirements of obstacle avoidance, dynamic feasibility, and energy efficiency. Current approaches often decouple these factors or exhibit high computational overhead, limiting applicability in real-time or large-scale [...] Read more.

Autonomous underwater vehicle (AUV) motion planning in complex three-dimensional ocean environments remains challenging due to the simultaneous requirements of obstacle avoidance, dynamic feasibility, and energy efficiency. Current approaches often decouple these factors or exhibit high computational overhead, limiting applicability in real-time or large-scale missions. This work proposes a hierarchical trajectory planning framework designed to address these coupled constraints in an integrated manner. The framework consists of two stages: (i) a current-biased sampling-based planner (CB-RRT*) is introduced to incorporate ocean current information into the path generation process. By leveraging flow field distributions, the planner improves path geometric continuity and reduces steering variations compared with benchmark algorithms; (ii) spatial–temporal alternating optimization is performed within underwater safe corridors, where Bézier curve parameterization is utilized to jointly optimize spatial shapes and temporal profiles, producing dynamically feasible and energy-efficient trajectories. Simulation results in dense obstacle fields, heterogeneous flow environments, and large-scale maps demonstrate that the proposed method reduces the maximum steering angle by up to 63% in downstream scenarios, achieving a mean maximum turning angle of 0.06 rad after optimization. The framework consistently attains the lowest energy consumption across all tests while maintaining an average computation time of 0.68 s in typical environments. These results confirm the framework’s suitability for practical AUV applications, providing a computationally efficient solution for generating safe, kinematically feasible, and energy-efficient trajectories in real-world ocean settings. Full article

(This article belongs to the Special Issue SLAM and Adaptive Navigation for Robotics)

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23 pages, 17893 KB

Open AccessArticle

Multimodal Control of Manipulators: Coupling Kinematics and Vision for Self-Driving Laboratory Operations

by Shifa Sulaiman, Amarnath Harikumar, Simon Bøgh and Naresh Marturi

Robotics 2026, 15(1), 17; https://doi.org/10.3390/robotics15010017 - 9 Jan 2026

Viewed by 306

Abstract

Autonomous experimental platforms increasingly rely on robust, vision-guided robotic manipulation to support reliable and repeatable laboratory operations. This work presents a modular motion-execution subsystem designed for integration into self-driving laboratory (SDL) workflows, focusing on the coupling of real-time visual perception with smooth and [...] Read more.

Autonomous experimental platforms increasingly rely on robust, vision-guided robotic manipulation to support reliable and repeatable laboratory operations. This work presents a modular motion-execution subsystem designed for integration into self-driving laboratory (SDL) workflows, focusing on the coupling of real-time visual perception with smooth and stable manipulator control. The framework enables autonomous detection, tracking, and interaction with textured objects through a hybrid scheme that couples advanced motion planning algorithms with real-time visual feedback. Kinematic analysis of the manipulator is performed using the screw theory formulations, which provide a rigorous foundation for deriving forward kinematics and the space Jacobian. These formulations are further employed to compute inverse kinematic solutions via the Damped Least Squares (DLS) method, ensuring stable and continuous joint trajectories even in the presence of redundancy and singularities. Motion trajectories toward target objects are generated using the RRT* algorithm, offering optimal path planning under dynamic constraints. Object pose estimation is achieved through a a vision workflow integrating feature-driven detection and homography-guided depth analysis, enabling adaptive tracking and dynamic grasping of textured objects. The manipulator’s performance is quantitatively evaluated using smoothness metrics, RMSE pose errors, and joint motion profiles, including velocity continuity, acceleration, jerk, and snap. Simulation results demonstrate that the proposed subsystem delivers stable, smooth, and reproducible motion execution, establishing a validated baseline for the manipulation layer of next-generation SDL architectures. Full article

(This article belongs to the Special Issue Visual Servoing-Based Robotic Manipulation)

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18 pages, 2160 KB

Open AccessArticle

Kinematic Analysis and Workspace Evaluation of a New Five-Axis 3D Printer Based on Hybrid Technologies

by Azamat Mustafa, Rustem Kaiyrov, Yerik Nugman, Mukhagali Sagyntay, Nurtay Albanbay, Algazy Zhauyt, Zharkynbek Turgunov, Ilyas Dyussebayev and Yang Lei

Robotics 2026, 15(1), 16; https://doi.org/10.3390/robotics15010016 - 7 Jan 2026

Viewed by 250

Abstract

Additive manufacturing technologies for metals are developing rapidly. Among them, wire arc additive manufacturing (WAAM) has become widespread due to its accessibility. However, parts produced using WAAM require surface post-processing; therefore, hybrid technologies have emerged that combine additive and subtractive processes within a [...] Read more.

Additive manufacturing technologies for metals are developing rapidly. Among them, wire arc additive manufacturing (WAAM) has become widespread due to its accessibility. However, parts produced using WAAM require surface post-processing; therefore, hybrid technologies have emerged that combine additive and subtractive processes within a single compact manufacturing complex. Such systems make it possible to organize single-piece and small-batch production, including for the repair and restoration of equipment in remote areas. For this purpose, hybrid equipment must be lightweight, compact for transportation, provide sufficient workspace, and be capable of folding for transport. This paper proposes the concept of a multifunctional metal 3D printer based on hybrid technology, where WAAM is used for printing, and mechanical post-processing is applied to obtain finished parts. To ensure both rigidity and low mass, a 3-UPU parallel manipulator and a worktable with two rotational degrees of freedom are employed, enabling five-axis printing and machining. The printer housing is foldable for convenient transportation. The kinematics of the proposed 3D printer are investigated as an integrated system. Forward and inverse kinematics problems are solved, the velocities and accelerations of the moving platform center are calculated, singular configurations are analyzed, and the workspace of the printer is determined. Full article

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

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24 pages, 21815 KB

Open AccessArticle

HGTA: A Hexagonal Grid-Based Task Allocation Method for Multi-Robot Coverage in Known 2D Environments

by Weixing Xia, Shihui Shen, Ping Wang and Jinjin Yan

Robotics 2026, 15(1), 15; https://doi.org/10.3390/robotics15010015 - 5 Jan 2026

Viewed by 315

Abstract

For multi-robot cooperative coverage, an effective spatial division strategy is essential to ensure balanced and spatially continuous task regions for each robot. Traditional grid-based partitioning approaches like DARP (Divide Areas based on Robots’ Positions) and TASR (Task Allocation based on Spatial Regions) often [...] Read more.

For multi-robot cooperative coverage, an effective spatial division strategy is essential to ensure balanced and spatially continuous task regions for each robot. Traditional grid-based partitioning approaches like DARP (Divide Areas based on Robots’ Positions) and TASR (Task Allocation based on Spatial Regions) often generate discontinuous sub-regions and imbalanced workloads, particularly in irregular or fragmented task spaces. To mitigate these issues, this paper introduces HGTA (Hexagonal Grid-based Task Allocation), a novel method that employs hexagonal tessellation for environmental representation. The hexagonal grid structure provides uniform neighbor connectivity and minimizes boundary fragmentation, yielding smoother partitions. HGTA integrates a multi-stage wavefront expansion algorithm with an iterative region-correction mechanism, jointly ensuring spatial contiguity and load equilibrium across robots. Extensive evaluations in 2D environments with varying obstacle densities and robot distributions show that HGTA enhances spatial continuity—achieving improvements of 18.2% in connectivity and 17.8% in boundary smoothness over DARP, and 7.5% and 9.5% over TASR, respectively—while also improving workload balance (variance reduction up to 18.5%) without compromising computational efficiency. The core contribution lies in the synergistic coupling of hexagonal tessellation, wavefront expansion, and dynamic correction, a design that fundamentally advances partition smoothness and convergence speed. HGTA thus offers a robust foundation for multi-robot cooperative coverage, area surveillance, and underwater search applications where connected and balanced partitions are critical. Full article

(This article belongs to the Section AI in Robotics)

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22 pages, 5346 KB

Open AccessArticle

A Body Power Hydraulic Prosthetic Hand

by Christopher Trent Neville-Dowler, Charlie Williams, Yuting Zhu and Kean C. Aw

Robotics 2026, 15(1), 14; https://doi.org/10.3390/robotics15010014 - 4 Jan 2026

Viewed by 345

Abstract

Limb amputations are a growing global challenge. Electrically powered prosthetic hands are heavy, expensive, and battery dependent. Body-powered prostheses offer a simpler and lighter alternative; however, existing designs require high body forces to operate, exhibit poor aesthetics, and have limited dexterity. This study [...] Read more.

Limb amputations are a growing global challenge. Electrically powered prosthetic hands are heavy, expensive, and battery dependent. Body-powered prostheses offer a simpler and lighter alternative; however, existing designs require high body forces to operate, exhibit poor aesthetics, and have limited dexterity. This study aims to present a design of a hydraulically actuated soft bending finger with a simple and scalable manufacturing process. This is then realised into a five-fingered body-powered prosthetic hand that is lightweight, comfortable, and representative of a human hand. The actuator was formed from two silicone materials of different stiffness (Stiff Smooth-Sil 950 and flexible Ecoflex 00-30) and reinforced with double-helix fibres to generate bending under internal hydraulic pressure. A shoulder-mounted hydraulic system has been designed to convert scapular elevation and protraction into actuator pressure. Finite element analysis and physical tests were performed to examine the bending and blocking force performance of the actuators. The physical actuators achieved bending angles up to 230 degrees at 60 kPa and blocking forces of 5.9 N at 100 kPa. The prosthetic system was able to grasp and hold a 320-g water bottle. The results demonstrate a soft actuator design that provides simple and scalable manufacturing and shows how these actuators can be incorporated into a body-powered prosthesis. This study provides a preliminary demonstration of the feasibility of human-powered prosthetics and necessitates continued research. This work makes progress towards an affordable and functional body-powered prosthetic hand that can improve the lives of transradial amputees. Full article

(This article belongs to the Section Soft Robotics)

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22 pages, 14360 KB

Open AccessArticle

Kinematic Characterization of a Novel 4-DoF Parallel Mechanism with Modular Actuation

by Zoltán Forgó and Ferenc Tolvaly-Roșca

Robotics 2026, 15(1), 13; https://doi.org/10.3390/robotics15010013 - 1 Jan 2026

Viewed by 207

Abstract

The accelerating industrial demand for high-speed manipulation has necessitated the development of robotic architectures that effectively balance dynamic performance with workspace size. While serial SCARA robots offer large workspaces and parallel Delta robots provide high acceleration, existing architectures fail to combine these benefits [...] Read more.

The accelerating industrial demand for high-speed manipulation has necessitated the development of robotic architectures that effectively balance dynamic performance with workspace size. While serial SCARA robots offer large workspaces and parallel Delta robots provide high acceleration, existing architectures fail to combine these benefits effectively for specific four-degree-of-freedom (4-DoF) Schoenflies motion tasks. This study introduces and characterizes a novel 4-DoF parallel topology, having a symmetrical build-up, which is distinguished by its use of modular 2-DoF linear drive units. The research methodology entails the structural synthesis of the kinematic chain followed by kinematic analysis using vector algebra to derive closed-form inverse geometric models. Additionally, the Jacobian matrix is formulated to evaluate velocity transmission and systematically classify singular configurations, while the dexterity index is defined to assess the rotational capabilities of the mechanism. Numerical simulations of pick-and-place trajectory were also conducted, varying trajectory curvature to analyze kinematic behavior. The results demonstrate that the proposed modular architecture yields a highly symmetric and homogeneous workspace that can be scaled simply by adjusting the drive module lengths. Furthermore, the singularity and dexterity analyses reveal a substantial, singularity-free operational workspace, although tighter trajectory curvatures were found to impose higher velocity demands on the joints. In conclusion, the proposed mechanism successfully achieves the targeted Schoenflies motion, offering a solution for automated industrial tasks. Full article

(This article belongs to the Special Issue Advanced Control and Optimization for Robotic Systems)

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23 pages, 8014 KB

Open AccessArticle

Design Evolution and Experimental Validation of the AlmatyExoElbow Assisting Device

by Dauren Bizhanov, Marco Ceccarelli, Kassymbek Ozhikenov and Nursultan Zhetenbayev

Robotics 2026, 15(1), 12; https://doi.org/10.3390/robotics15010012 - 30 Dec 2025

Viewed by 289

Abstract

This paper presents the design, prototype, and experimental evaluation of the AlmatyExoElbow, a lightweight cable-driven robotic exoskeleton that is intended to support elbow joint rehabilitation. The device provides two active degrees of freedom for flexion/extension and pronation/supination. It also incorporates a sensor-based control [...] Read more.

This paper presents the design, prototype, and experimental evaluation of the AlmatyExoElbow, a lightweight cable-driven robotic exoskeleton that is intended to support elbow joint rehabilitation. The device provides two active degrees of freedom for flexion/extension and pronation/supination. It also incorporates a sensor-based control system for accurate motion tracking. The mechanical structure is fabricated using 3D-printed PLA plastic, resulting in a compact, modular, and comfortable design suitable for prolonged use. The control architecture is based on an Arduino Nano microcontroller integrated with IMU sensors, enabling the real-time monitoring of elbow motion and the precise reproduction of physiologically relevant movement patterns. The results of experimental testing demonstrate smooth and stable operation, confirming reliable torque transmission through antagonistic cable mechanisms. Overall, the proposed design achieves a balanced combination of functionality, portability, and user comfort, highlighting its potential for upper-limb rehabilitation applications in both clinical and home-based settings. Full article

(This article belongs to the Topic Bio-Inspired, Biomedical, Surgical, Social and AI-Integrated Bio-Mechanical Robotics)

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20 pages, 1440 KB

Open AccessArticle

Robust Optimization and Workspace Enhancement of a Reconfigurable Delta Robot via a Singularity-Sensitive Index

by Arturo Franco-López, Mauro Maya, Alejandro González, Liliana Félix-Ávila, César-Fernando Méndez-Barrios and Antonio Cardenas

Robotics 2026, 15(1), 11; https://doi.org/10.3390/robotics15010011 - 30 Dec 2025

Viewed by 293

Abstract

This study investigates the kinematic behavior of a reconfigurable Delta parallel robot aiming to enhance its performance in real industrial applications such as high-speed packaging, precision pick-and-place operations, automated inspection, and lightweight assembly tasks. While Delta robots are widely recognized for their speed [...] Read more.

This study investigates the kinematic behavior of a reconfigurable Delta parallel robot aiming to enhance its performance in real industrial applications such as high-speed packaging, precision pick-and-place operations, automated inspection, and lightweight assembly tasks. While Delta robots are widely recognized for their speed and accuracy, their practical use is often limited by workspace constraints and singularities that compromise motion stability and control safety. Through a detailed analysis, it is shown that classical Jacobian-based performance indices are unsuitable for resolving the redundancy introduced by geometric reconfiguration, as they may lead the system toward singular or ill-conditioned configurations. To overcome these limitations, this work introduces an adjustable singularity-sensitive performance index designed to penalize extreme velocity and force singular values and enables tuning between velocity and force performance. Simulation results demonstrate that optimizing the reconfiguration parameter using this index increases the usable workspace by approximately 82% and improves the uniformity of manipulability across the workspace. These findings suggest that the proposed approach provides a robust framework for enhancing the operational range and kinematic safety of reconfigurable Delta robots, while remaining adaptable to different design priorities. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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24 pages, 19110 KB

Open AccessArticle

Low-Code Mixed Reality Programming Framework for Collaborative Robots: From Operator Intent to Executable Trajectories

by Ziyang Wang, Zhihai Li, Hongpeng Yu, Duotao Pan, Songjie Peng and Shenlin Liu

Robotics 2026, 15(1), 9; https://doi.org/10.3390/robotics15010009 - 29 Dec 2025

Viewed by 283

Abstract

Efficient and intuitive programming strategies are essential for enabling robots to adapt to small-batch, high-mix production scenarios. Mixed reality (MR) and programming by demonstration (PbD) have shown great potential to lower the programming barrier and enhance human–robot interaction by leveraging natural human guidance. [...] Read more.

Efficient and intuitive programming strategies are essential for enabling robots to adapt to small-batch, high-mix production scenarios. Mixed reality (MR) and programming by demonstration (PbD) have shown great potential to lower the programming barrier and enhance human–robot interaction by leveraging natural human guidance. However, traditional offline programming methods, while capable of generating industrial-grade trajectories, remain time-consuming, costly to debug, and heavily dependent on expert knowledge. Conversely, existing MR-based PbD approaches primarily focus on improving intuitiveness but often suffer from low trajectory quality due to hand jitter and the lack of refinement mechanisms. To address these limitations, this paper introduces a coarse-to-fine human–robot collaborative programming paradigm. In this paradigm, the operator’s role is elevated from a low-level “trajectory drawer” to a high-level “task guider”. By leveraging sparse key points as guidance, the paradigm decouples high-level human task intent from machine-level trajectory planning, enabling their effective integration. The feasibility of the proposed system is validated through two industrial case studies and comparative quantitative experiments against conventional programming methods. The results demonstrate that the coarse-to-fine paradigm significantly improves programming efficiency and usability while reducing operator cognitive load. Crucially, it achieves this without compromising the final output, automatically generating smooth, high-fidelity trajectories from simple user inputs. This work provides an effective pathway toward reconciling programming intuitiveness with final trajectory quality. Full article

(This article belongs to the Section AI in Robotics)

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17 pages, 160077 KB

Open AccessArticle

RA6D: Reliability-Aware 6D Pose Estimation via Attention-Guided Point Cloud in Aerosol Environments

by Woojin Son, Seunghyeon Lee, Taejoo Kim, Geonhwa Son and Yukyung Choi

Robotics 2026, 15(1), 8; https://doi.org/10.3390/robotics15010008 - 29 Dec 2025

Viewed by 277

Abstract

We address the problem of 6D object pose estimation in aerosol environments, where RGB and depth sensors experience correlated degradation due to scattering and absorption. Handling such spatially varying degradation typically requires depth restoration, but obtaining ground-truth complete depth in aerosol conditions is [...] Read more.

We address the problem of 6D object pose estimation in aerosol environments, where RGB and depth sensors experience correlated degradation due to scattering and absorption. Handling such spatially varying degradation typically requires depth restoration, but obtaining ground-truth complete depth in aerosol conditions is prohibitively expensive. To overcome this limitation without relying on costly depth completion, we propose RA6D, a framework that integrates attention-guided reliability modeling with feature distillation. The attention map generated during RGB dehazing reflects aerosol distribution and provides a compact indicator of depth reliability. By embedding this attention as an additional feature in an Attention-Guided Point cloud (AGP), the network can adaptively respond to spatially varying degradation. In addition, to address the scarcity of aerosol-domain data, we employ clean-to-aerosol feature distillation, transferring robust representations learned under clean conditions. Experiments on aerosol benchmarks show that RA6D achieves higher accuracy and significantly faster inference than restoration-based pipelines, offering a practical solution for real-time robotic perception under severe visual degradation. Full article

(This article belongs to the Special Issue Extended Reality and AI Empowered Robots)

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18 pages, 3437 KB

Open AccessArticle

Development of an Autonomous Robot for Precision Floor Marking

by Fatimah Alahmed, Muhammad Hawwa and Uthman Baroudi

Robotics 2026, 15(1), 7; https://doi.org/10.3390/robotics15010007 - 29 Dec 2025

Viewed by 509

Abstract

The construction and facilities management sectors are increasingly adopting automation technologies to improve productivity and reduce manual labor. In parallel, decorative and informational floor-marking is widely used in indoor environments such as schools, exhibition halls, and public spaces to support organization, wayfinding, and [...] Read more.

The construction and facilities management sectors are increasingly adopting automation technologies to improve productivity and reduce manual labor. In parallel, decorative and informational floor-marking is widely used in indoor environments such as schools, exhibition halls, and public spaces to support organization, wayfinding, and visual communication. While robotic systems have been developed for floor and layout marking, many existing solutions rely on specialized infrastructure or offer limited flexibility in the range of patterns that can be produced. This paper presents the development of a prototype of a mobile, wheeled robot capable of autonomously executing diverse designs on surfaces such as fields and floors. The robot’s potential applications include use on indoor floors and exhibition halls. It marks the ground using a plotting pen while navigating and avoiding obstacles within its environment. Additionally, the robot can produce a range of drawings, including letters and signage, and its capabilities can be extended to create decorative patterns as well as marks for floor-based games. This robot was constructed entirely from cost-effective, commercially available components. Experimental evaluation demonstrates repeatable motion and drawing performance, with measured standard deviations of approximately 1.6 mm in forward motion and 3 mm in lateral motion during representative grid-based traversal. These results indicate that the proposed approach achieves a level of accuracy and consistency sufficient for decorative floor-marking and similar applications, without reliance on external localization infrastructure. Full article

(This article belongs to the Topic New Trends in Robotics: Automation and Autonomous Systems)

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31 pages, 1669 KB

Open AccessArticle

Geometry, Kinematics, Workspace, and Singularities of a Novel 3-PRRS Parallel Manipulator

by Zhumadil Baigunchekov, Giuseppe Carbone, Med Amine Laribi, Rustem Kaiyrov, Li Qian and Zhadyra Zhumasheva

Robotics 2026, 15(1), 10; https://doi.org/10.3390/robotics15010010 - 29 Dec 2025

Viewed by 324

Abstract

“Experiments were conducted at DIMEG, University of Calabria, located in the main campus in Arcavacata di Rende, Italy.” This article focuses on the study of the geometry, direct and inverse kinematics, workspace, and singularity of a novel 3-PRRS parallel manipulator (PM) with a [...] Read more.

“Experiments were conducted at DIMEG, University of Calabria, located in the main campus in Arcavacata di Rende, Italy.” This article focuses on the study of the geometry, direct and inverse kinematics, workspace, and singularity of a novel 3-PRRS parallel manipulator (PM) with a redundantly actuated architecture. The PM consists of three active revolute joints and three passive prismatic redundant input joints, all located on a fixed platform. The constant and variable parameters characterizing the PM’s geometry and kinematics are determined. The direct kinematics problem is formulated as a 16th-degree polynomial, while the inverse kinematics problem is solved in closed form. A comparison of the direct and inverse kinematics is provided, and the correctness of the solutions is validated through numerical examples. The equations of motion for the moving platform are derived, and the PM’s workspace is defined based on the inverse kinematics. This work demonstrates how the passive prismatic input joints, specifically included in the design, contribute to an enlarged workspace—particularly in the vertical direction—compared to traditional 3-RRS PM architecture. Full article

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

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2 pages, 142 KB

Open AccessEditorial

Selected Papers from MEDER 2024: Advances in Mechanism Design for Robotics

by Marco Ceccarelli and Erwin-Christian Lovasz

Robotics 2026, 15(1), 6; https://doi.org/10.3390/robotics15010006 - 28 Dec 2025

Viewed by 245

Abstract

In this Special Issue, we aim to promote and circulate recent mechanism design developments and achievements in the international field of robotics, ranging from theoretical contributions to experimental and practical applications [...] Full article

(This article belongs to the Special Issue Selected Papers from MEDER 2024: Advances in Mechanism Design for Robotics)

19 pages, 3517 KB

Open AccessArticle

An Integrated MADQN–Heuristic Framework for Swarm Robotic Fire Detection and Extinguishing

by Andrei Dutceac and Constantin I. Vizitiu

Robotics 2026, 15(1), 5; https://doi.org/10.3390/robotics15010005 - 27 Dec 2025

Viewed by 275

Abstract

Wildfires pose a growing global threat, demanding rapid, scalable, and autonomous response strategies. This study proposes HG-MADQN (Heuristic-Guided Multi-Agent Deep Q-Network), a hybrid framework that integrates reinforcement learning with biologically inspired pheromone-based heuristics to achieve adaptive fire detection and suppression using drone swarms. [...] Read more.

Wildfires pose a growing global threat, demanding rapid, scalable, and autonomous response strategies. This study proposes HG-MADQN (Heuristic-Guided Multi-Agent Deep Q-Network), a hybrid framework that integrates reinforcement learning with biologically inspired pheromone-based heuristics to achieve adaptive fire detection and suppression using drone swarms. The system models a decentralized swarm operating in a grid-based environment, where each drone combines learned policies with heuristic guidance derived from a dual-pheromone mechanism (a fire-attraction field guiding suppression and a coverage-repulsion field promoting exploration). The proposed hybrid approach ensures efficient coordination, minimizes redundant movements, and maintains continuous area coverage without centralized control. Simulation experiments conducted on dynamic wildfire scenarios demonstrate that HG-MADQN significantly outperforms traditional heuristic, Lévy-Flight, and reinforcement learning (MADQN) algorithms. It achieves faster containment, reduced burned area, and lower resource consumption, while exhibiting strong robustness across multiple swarm sizes and fire configurations. The results confirm that hybridizing learned and heuristic decision models enables a balanced exploration–exploitation trade-off, leading to improved scalability and resilience in cooperative fire suppression missions. Full article

(This article belongs to the Special Issue Multi-Robot Systems for Environmental Monitoring and Intervention)

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25 pages, 11080 KB

Open AccessArticle

Decentralized Multi-Cobot Navigation Under Intermittent Communication

by Zuguang Liu and Md Suruz Miah

Robotics 2026, 15(1), 4; https://doi.org/10.3390/robotics15010004 - 26 Dec 2025

Viewed by 287

Abstract

As collaborative robots (cobots) become more prevalent in industry, there is growing need for autonomous cobots that can cooperatively navigate shared workspaces. Reliable navigation and safety become especially critical when intermittent communication failures occur, potentially due to environmental factors or network disruptions. This [...] Read more.

As collaborative robots (cobots) become more prevalent in industry, there is growing need for autonomous cobots that can cooperatively navigate shared workspaces. Reliable navigation and safety become especially critical when intermittent communication failures occur, potentially due to environmental factors or network disruptions. This paper contributes to the development of a navigation scheme for a team of autonomous networked cobots under intermittent communication. In particular, the paper proposes a decentralized control approach enabling cobots to cooperatively transport an object across an industrial environment despite intermittent communication. The navigation scheme is decentralized in the sense that each cobot computes its control actions locally using only information from neighboring cobots, without relying on a central coordinator, and applies actuator commands independently based on local sensor feedback and inter-robot communication. The work presented herein provides a comprehensive framework for autonomous multi-cobot cooperative object transportation tasks, including the design of the control, navigation, and communication systems. The communication network among the cobots is modeled using directed graphs, with the graph Laplacian matrix representing the connectivity among the cobots. The proposed method is first validated using a commercial robot simulator. Its performance is then evaluated on physical cobots operating in an indoor environment with various complexities. Full article

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

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20 pages, 25939 KB

Open AccessArticle

Preliminary Design and Testing of Brush.Q: An Articulated Ground Mobile Robot with Compliant Brush-like Wheels

by Lorenzo Toccaceli, Andrea Botta, Giovanni Colucci, Luigi Tagliavini, Carmen Visconte and Giuseppe Quaglia

Robotics 2026, 15(1), 3; https://doi.org/10.3390/robotics15010003 - 24 Dec 2025

Viewed by 351

Abstract

Recent advances in mobile robotics have emphasized the need for systems capable of operating in unstructured environments, combining obstacle negotiation, stability, and adaptability. This study presents the preliminary design and testing of Brush.Q, an articulated ground robot featuring a novel structure distinct from [...] Read more.

Recent advances in mobile robotics have emphasized the need for systems capable of operating in unstructured environments, combining obstacle negotiation, stability, and adaptability. This study presents the preliminary design and testing of Brush.Q, an articulated ground robot featuring a novel structure distinct from existing wheel-legged robots, equipped with compliant brush-like wheels composed of multiple spokes. The main contribution is the experimental analysis of suspension capability across different wheel geometric profiles, combined with the assessment of obstacle-climbing performance. A simplified prototype was constructed to evaluate the effects of wheel rotation direction, spoke number, and spoke tapering. Results show that reducing the number of spokes improves obstacle-climbing at the expense of suspension, while higher spoke count and compliant geometry enhance suspension and stability. Spoke tapering improves obstacle climbing in the backward-facing configuration but consistently reduces suspension. Overall, these findings highlight the critical role of wheel geometry and the potential for reconfigurable spoked wheels to enhance adaptability and versatility in unstructured terrains. Full article

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

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20 pages, 10299 KB

Open AccessArticle

A Single Actuator Driven Two-Fold Symmetric Mechanism for Versatile Dynamic Locomotion

by Muhammad Hamza Asif Nizami, Zaid Ahsan Shah, Charles Young and Jonathan Clark

Robotics 2026, 15(1), 2; https://doi.org/10.3390/robotics15010002 - 23 Dec 2025

Viewed by 384

Abstract

Tumbling, rolling, and somersaults are alternate forms of locomotion used by animals and robots to navigate rough terrains. In this paper, we present a Two-Fold Symmetric (TFS) mechanism that demonstrates dynamic tumbling and leaping using a single actuator. The dynamics of the proposed [...] Read more.

Tumbling, rolling, and somersaults are alternate forms of locomotion used by animals and robots to navigate rough terrains. In this paper, we present a Two-Fold Symmetric (TFS) mechanism that demonstrates dynamic tumbling and leaping using a single actuator. The dynamics of the proposed mechanism are captured by a hybrid dynamic model with discrete states based on the nature of ground contact. By changing the shape parameters of a trapezoidal actuation signal, various dynamic responses and gaits are attained. Simulations and hardware experiments demonstrate tumbling and leaping/hopping. It is shown that the mechanism demonstrates gait versatility and attains speeds up to

3.0

Body Lengths per second and can jump up to a height of

60 %

of its total height, all using a single actuator that sets it apart from contemporary tumbling robots. Full article

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

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28 pages, 24905 KB

Open AccessArticle

Compact LET Arrays for Origami-Based Mechanisms

by Luke Q. Gardner, Katie Varela, Larry L. Howell and Spencer P. Magleby

Robotics 2026, 15(1), 1; https://doi.org/10.3390/robotics15010001 - 19 Dec 2025

Viewed by 504

Abstract

Lamina Emergent Torsional (LET) arrays can be used to replace creases in origami-based mechanisms. They can be made of planar materials, which makes them compatible with many designs. However, LET arrays can take up a lot of area and can exhibit significant parasitic [...] Read more.

Lamina Emergent Torsional (LET) arrays can be used to replace creases in origami-based mechanisms. They can be made of planar materials, which makes them compatible with many designs. However, LET arrays can take up a lot of area and can exhibit significant parasitic motion, which makes them less ideal for some applications, such as in origami-based robotics and deployable space structures. This work presents a compact variation of the conventional LET array, which resolves these issues. An experimental method for fabricating these compact LET arrays, or C-LET arrays, from carbon fiber-reinforced polymer is given. Deflection models for C-LET array torsion segments, with and without interference with other torsion segments, are given. Bending stress and shear stress equations are provided, and the deflection models are combined into a final model that can solve for the deflections of multiple torsion segments in series. The concepts described are demonstrated in a prototype origami-based deployable reflectarray incorporating C-LET arrays. The prototype demonstrates that C-LET arrays provide the desired motion while maximizing the usable area of the deployable reflectarray. Full article

(This article belongs to the Section Aerospace Robotics and Autonomous Systems)

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Robotics, Volume 15, Issue 1 (January 2026) – 29 articles

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