Robotics and Autonomous Systems最新文献

{"title":"A novel algorithm for key road sections obstacle detection based on LiDAR","authors":"Zongliang Nan ,&nbsp;Guoan Zhu ,&nbsp;Xu Zhang ,&nbsp;Xiaoqi Liu ,&nbsp;Xuechun Lin ,&nbsp;Yingying Yang","doi":"10.1016/j.robot.2025.105136","DOIUrl":"10.1016/j.robot.2025.105136","url":null,"abstract":"<div><div>Ensuring the safety of key road sections is crucial, and high-precision Obstacle Detection (OD) is necessary to achieve this goal. In this study, we utilized LiDAR technology to develop a novel algorithm that accurately detects obstacles in critical road sections. The algorithm consists of three main parts: Firstly, the point cloud is segmented into scan lines, and the distribution error of the scan lines is used to filter out point clouds that correspond to road boundary. Secondly, we used an improved DBSCAN algorithm to achieve global robust clustering. This method introduces a modulation function to dynamically regulate the neighbourhood radius during the clustering process by referring to the density distribution characteristics of point clouds in the <span><math><mi>x</mi></math></span> and <span><math><mi>y</mi></math></span> directions. This step was employed to extract suspicious obstacle clusters. Finally, we extract regions corresponding to the real-time input point cloud from the reference point cloud. Segmented ICP (Seg-ICP) registration was performed in the global scope to obtain a true set of obstacle clusters. Experiment results in multiple locations demonstrated that our algorithm could effectively identify dangerous obstacles in key road sections. Our algorithm can detect obstacles of 10 <em>cm</em> * 10 <em>cm</em> * 10 <em>cm</em> within a range of 50<em>m</em> and its Average Final Detection Rate (AFDR) can reach at 99.47%, providing an optional means of safety protection for key road sections.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105136"},"PeriodicalIF":5.2,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Hierarchical Fuzzy Formation Control with fuzzy collision avoidance behavior for multiple Mecanum wheeled Mobile Robots","authors":"Hsiu-Ming Wu ,&nbsp;Muhammad Qomaruz Zaman","doi":"10.1016/j.robot.2025.105124","DOIUrl":"10.1016/j.robot.2025.105124","url":null,"abstract":"<div><div>Integrating collision avoidance mechanisms into formation control represents a critical aspect for enabling multi-mobile robotic coordination from arbitrary initial configurations. Additionally, the reliance on precise system models for controller design and leader-centralized control architecture limits the flexibility to dynamically reconfigure the formation structure, which is often crucial in real-world applications. Consequently, exploration of modularly interpretable and model-free control strategies emerge as a compelling research direction to address contemporary robotic coordination challenges. This study proposes a Hierarchical Fuzzy Formation Control (HFFC) approach for multiple Mecanum-wheeled Mobile Robots (MMRs) to achieve simultaneous formation tracking, collision avoidance, and orientation alignment. The HFFC leverages a modular hierarchical fuzzy inference system, combining leader–follower and behavior-based strategies. Fuzzified sliding surfaces enhance the tracking performance by minimizing oscillation and chattering effects during formation convergence. Collision avoidance is improved by incorporating inter-MMR approaching rate, enabling proactive anticipation and more responsive maneuvers. A realistic Takagi–Sugeno model, replicating real-world MMR behavior with practical actuator voltage inputs, is developed for evaluation. Simulations demonstrate that five MMRs achieve the desired formation geometry within 1.9 s with 0.048 m accuracy while maintaining a minimum inter-robot distance of 10.77 cm to prevent collisions. Moreover, compared to existing approaches, the proposed control scheme possesses better performance.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105124"},"PeriodicalIF":4.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Path and footfall planning for N-legged and climbing robots — A model predictive control approach","authors":"Carlos Prados,&nbsp;Miguel Hernando,&nbsp;Ernesto Gambao","doi":"10.1016/j.robot.2025.105119","DOIUrl":"10.1016/j.robot.2025.105119","url":null,"abstract":"<div><div>In this paper, we present a general control framework for N-legged and variably-configured robots, designed to coordinate leg movements for climbing tasks without relying on Central Pattern Generators (CPGs). Model-based path and footfall planners are introduced to minimize actuator effort, minimize robot detachment risk, improve payload distribution between legs, and maximize the traveled distance during the swing phase. To achieve this, we address the force distribution problem (FDP) by selecting configurations where the robot is most comfortable in terms of kinematics, effort, and safety. A gait controller is presented as a nonperiodic, nonsymmetric, and nonregular bioinspired method that selects the most convenient leg to move by ensuring comfort, safety, and robot capabilities. The system has been tested in simulation with different robot configurations (varying number of legs and arrangements) and with the physical robot ROMERIN in its quadruped version.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105119"},"PeriodicalIF":4.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phase-independent Dynamic Movement Primitives with applications to human–robot co-manipulation and time optimal planning","authors":"Giovanni Braglia,&nbsp;Davide Tebaldi,&nbsp;Luigi Biagiotti","doi":"10.1016/j.robot.2025.105120","DOIUrl":"10.1016/j.robot.2025.105120","url":null,"abstract":"<div><div>Dynamic Movement Primitives (DMP) are an established and efficient method for encoding robotic tasks that require adaptation based on reference motions. Typically, the nominal trajectory is obtained through Programming by Demonstration (PbD), where the robot learns a task via kinesthetic guidance and reproduces it in terms of both geometric path and timing law. Modifying the duration of the execution in standard DMPs is achieved by adjusting a time constant in the model.</div><div>This paper introduces a novel approach to fully decouple the geometric information of a task from its temporal information using an algorithm called spatial sampling, which allows parameterizing the demonstrated curve by its arc-length. This motivates the use of the name Geometric DMP (GDMP) for the proposed DMP approach. The proposed spatial sampling algorithm guarantees the regularity of the demonstrated curve and ensures a consistent projection of the human force throughout the task in a human-in-the-loop scenario. GDMP exhibits phase independence, as its phase variable is no longer constrained to the demonstration’s timing law, enabling a wide range of applications, including phase optimization problems and human-in-the-loop applications. Firstly, a minimum task duration optimization problem subject to velocity and acceleration constraints is formulated. The decoupling of path and speed in GDMP allows to achieve optimal time duration without violating the constraints. Secondly, GDMP is validated in a human-in-the-loop application, providing a theoretical passivity analysis and an experimental stability evaluation in co-manipulation tasks. Finally, GDMP is compared with other DMP architectures available in the literature, both for the phase optimization problem and experimentally with reference to an insertion task and a simulated welding task, showcasing the enhanced performance of GDMP with respect to other solutions.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105120"},"PeriodicalIF":4.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data efficient online learning of robot behaviours via qualitative planning and reinforcement learning","authors":"Timothy Wiley ,&nbsp;Claude Sammut","doi":"10.1016/j.robot.2025.105122","DOIUrl":"10.1016/j.robot.2025.105122","url":null,"abstract":"<div><div>Autonomous robots execute complex behaviours to perform tasks in real-world environments. Reinforcement learning can acquire such behaviours, however, often requires a large number of iterations to reach an operational behaviour. This makes it inefficient for online learning, that is, learning on board the robot as it operates. Combinations of techniques such as model-based reinforcement learning, planning, and behavioural cloning, attempt to narrow the search space of trial-and-error learning. However, they rely on a significant degree of domain knowledge. We develop a domain independent Data Efficient Planning and Learning Architecture for online skill acquisition and which is applied to locomotion tasks on a multi-tracked robot typical of those designed for urban search and rescue. We build a qualitative model of the robot’s dynamics from online behavioural traces, that trades accuracy for domain independence in elevating the skill acquisition problem into a symbolic representation. Then a forward-chaining planner finds an operational sequence of qualitative symbolic actions enabling the robot to complete a task, from which quantitative action parameters representing the robot’s actuator movements are extracted. The qualitative plan places constraints on valid parameter values. This enables online reinforcement learning to refine the parameters into satisficing (or optimal) actuator movements, making trial-and-error learning data efficient in terms of the number of trials. By applying our architecture in a “closed-loop”, the qualitative model is improved from the reinforcement learning trials, refining the final robot’s operation, along with discovering new emergent behaviours.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105122"},"PeriodicalIF":5.2,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional pole placement-based robust lateral controller for autonomous ground vehicles considering uncertainty","authors":"Md. Abdur Rahim ,&nbsp;Mohammad Rokonuzzaman ,&nbsp;Ahmad Abu Alqumsan ,&nbsp;Adetokunbo Arogbonlo","doi":"10.1016/j.robot.2025.105121","DOIUrl":"10.1016/j.robot.2025.105121","url":null,"abstract":"<div><div>Autonomous ground vehicles (AGVs) often face challenges in maintaining tracking accuracy and stability due to uncertainties and external factors, such as variations in road surface friction and wind. These factors, particularly at higher speeds, significantly hinder the ability to achieve the desired stability and tracking performance. To address these challenges, we propose a novel robust lateral controller (RLC) by exploiting the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> synthesis technique, considering uncertain cornering stiffness, with linear matrix inequality (LMI)-based regional pole placement constraints (RPPC). The proposed regional pole placement constraints-based robust lateral controller (RPPC-RLC) with uncertainty is designed to be robust against variations in road conditions and external disturbances, ensuring the desired path-tracking accuracy and vehicle stability. A state-feedback control law is employed using a nonlinear vehicle dynamics model to develop LMIs as performance conditions. Additionally, we utilised RPPC technique to precisely refine the controller gain for ensuring precise stability and robust performance in the presence of uncertainties and active disturbances. The proposed controller’s effectiveness is rigorously examined under different road conditions, various AGV speeds, and both the presence and absence of wind disturbances, while cornering stiffness was considered an uncertain parameter. The performance of the controller was also compared with several commonly used controllers, such as the model predictive controller (MPC), <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>, conventional robust controller, and the Linear Quadratic Regulator (LQR). The results demonstrate that the proposed controller outperforms these alternatives in terms of minimising the lateral position error and heading error, based on different statistical parameters. Furthermore, we validated the controller’s performance in a MATLAB/Simulink environment using a 14-degree-of-freedom complex vehicle model. Finally, the proposed RPPC-RLC with uncertainty exhibited efficient tracking performance and maintained the stability of the AGV under varying road conditions and wind disturbances at different speeds, even at high speeds.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105121"},"PeriodicalIF":4.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory planning system for bimanual robots: Achieving efficient collision-free manipulation","authors":"Francisco José Martínez-Peral ,&nbsp;Jorge Borrell Méndez ,&nbsp;Dennis Mronga ,&nbsp;José Vicente Segura-Heras ,&nbsp;Carlos Perez-Vidal","doi":"10.1016/j.robot.2025.105118","DOIUrl":"10.1016/j.robot.2025.105118","url":null,"abstract":"<div><div>Pick-and-place operations are non-value-added activities but essential in many industrial processes. Some of these operations must be performed by dual-arm robots, which represent new challenges in terms of collision-avoidance due to the use of a shared workspace. This work addresses these two issues by proposing a Task and Motion Architecture (TMA) designed to optimize pick-and-place tasks, ensuring efficient and safe operation through collision-free movements. This architecture consists of two interconnected sublayers, the Task Planner (TP) and the Global Motion Planner (GMP). The TP calculates the optimal sequence of operations, minimizing the total execution time and guaranteeing a collision-free sequence. The GMP plans the trajectories of the robotic arms using predefined motion strategies and following the calculated optimal sequence. This work presents a novel solution for enhancing the efficiency of robot coordination in real-world settings by integrating an intercommunicated TP and MP. Results from simulations demonstrate improved task efficiency, reduced operational times, and successful collision avoidance between robots.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105118"},"PeriodicalIF":4.3,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NMPC design for a self-aligning compliant gait rehabilitation robot","authors":"Yinan Jin ,&nbsp;Tanishka Goyal ,&nbsp;Prashant K. Jamwal ,&nbsp;Roland Goecke ,&nbsp;Mergen H. Ghayesh ,&nbsp;Shahid Hussain","doi":"10.1016/j.robot.2025.105128","DOIUrl":"10.1016/j.robot.2025.105128","url":null,"abstract":"<div><div>The application of robotic devices in rehabilitation is proliferating. Such devices’ mechanism design, actuation, and control strategy are essential for effective and successful rehabilitation treatment. This paper investigates the effectiveness of a self-aligning mechanism for a multi-DOFs (Degrees of Freedom) rehabilitation robot. The actuation is provided by lightweight albeit powerful Pneumatic Muscle Actuators (PMA). Although the mechanism design and the actuation system provide a safe, secure, and efficient platform for rehabilitation, they increase the complexity of the system modeling and, subsequently, the control system’s design. Furthermore, the mechanism has three active and five passive DOFs, which further increase the intricacies of system identification. Hence, this paper presents an autodidactic approach to identify the system dynamics using the Koopman operator. The learned operator is then integrated with the Nonlinear Model Predictive Controller (NMPC) to guide the robot along the predefined path while adapting to the nonlinear dynamics of the physical human-robot interaction. Finally, the rehabilitation robot and the control scheme were experimentally validated with healthy human subjects. The results demonstrate that the NMPC controller could successfully manipulate the gait rehabilitation robot with the subject to achieve the desired orientation during the entire gait cycle.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105128"},"PeriodicalIF":4.3,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LiDAR odometry method based on multi-scale fusion and semantic enhancement","authors":"Yibin Ye ,&nbsp;Yang Ren ,&nbsp;Yiming Fan ,&nbsp;Yiyou Liang ,&nbsp;Hui Zeng","doi":"10.1016/j.robot.2025.105093","DOIUrl":"10.1016/j.robot.2025.105093","url":null,"abstract":"<div><div>In this paper, we propose an end-to-end deep learning-based LiDAR odometry framework addressing key challenges such as point cloud information loss, density variability, and dynamic scene uncertainty. By directly using raw point clouds, our method avoids dimensionality reduction loss and introduces a light-weight geometrically adaptive convolution to improve feature extraction based on local geometric structures. Additionally, a multi-scale fusion and semantic enhancement strategy is employed to incorporate semantic context and optimize pose estimation from coarse to fine. Experimental results on the KITTI dataset show that our approach is competitive with existing methods in accuracy and robustness.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105093"},"PeriodicalIF":4.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and optimization of a novel pneumatic translational manipulator with independent constraints","authors":"Tao Wang,&nbsp;Ying Zhao,&nbsp;Bo Wang","doi":"10.1016/j.robot.2025.105125","DOIUrl":"10.1016/j.robot.2025.105125","url":null,"abstract":"<div><div>Pneumatic parallel translation robots offer several advantages in complex industrial production environments, such as a simple structure, high cleanliness, and excellent safety. This paper presents a novel split-type translational manipulator structure 3S<u>P</u>S+3CPR. The independent restraining limbs (3-CPR) effectively constrain undesired degrees of freedom at the platform's end without compromising the kinematic properties of the manipulator. This paper provides kinematic, workspace analysis, and performance evaluation, and furthermore, proposes a dimensional optimization scheme for the manipulator based on motion/force transmission performance and geometric constraints. Prototype experiments have been conducted to validate the rationality and efficacy of the overall design. Compared to traditional integrated drive-constrained translational mechanisms, this pure linear transmission design features simple analysis, flexible design, and fewer associated parameters. Additionally, using cylinders as actuators endows the manipulator with rapid response characteristics, making it suitable for industrial applications requiring fast translation.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105125"},"PeriodicalIF":4.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}