Robotics and Autonomous Systems最新文献

{"title":"Conform to grip: Joint reaction force-driven adaptive variable admittance control of biped climbing robots","authors":"Haifei Zhu,&nbsp;Pengcheng Ye,&nbsp;Jiongyu Tan,&nbsp;Weinan Chen,&nbsp;Tao Zhang,&nbsp;Yisheng Guan","doi":"10.1016/j.robot.2025.105105","DOIUrl":"10.1016/j.robot.2025.105105","url":null,"abstract":"<div><div>Current biped climbing robots encounter persistent challenges in aligning their grippers with structural elements like poles, regardless of teleoperation or perception-based control implementations. To overcome this limitation, we present a joint reaction force-driven adaptive variable admittance control framework that enables autonomous compliant alignment with enhanced precision. The proposed method utilizes unintentional gripper-pole contact-induced joint reaction forces to drive alignment through a variable damping admittance controller. Damping parameters are adaptively regulated through proportional-derivative control law based on real-time joint reaction force errors. By establishing zero reference reaction force, the system concurrently accomplishes dual objectives: gripper pose alignment and reaction force minimization. Experimental validation confirms that our framework significantly enhances alignment efficiency and gripping reliability without requiring explicit gripper-pole pose detection. This methodology proves particularly effective for robotic systems transitioning between open-chain and closed-chain configurations while resolving inherent joint conflicts.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105105"},"PeriodicalIF":4.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604738","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":"Quantum neural network-based inverse kinematics of a six-jointed industrial robotic arm","authors":"Mehdi Fazilat,&nbsp;Nadjet Zioui","doi":"10.1016/j.robot.2025.105123","DOIUrl":"10.1016/j.robot.2025.105123","url":null,"abstract":"<div><div>This research examines the potential of quantum-inspired neural networks (QNNs) for solving the inverse kinematics of robotic arms, focusing on the six-degree-of-freedom ABB IRB140 robot. Traditional inverse kinematics approaches face challenges such as non-unique solutions and computational complexity, especially with increasing degrees of freedom. While artificial neural networks (ANNs) have shown promise, they require further improvements, particularly in terms of quantum computing integration. This study introduces a quantum-inspired activation function to multi-layer perceptron neural networks. We compared ANNs and QNNs with and without singularity avoidance, finding that QNNs significantly outperformed ANNs in mean absolute error (MAE), achieving a 15.60 % lower MAE in singularity-free models and a 16.67 % lower MAE in singularity-avoidance models. The QNNs demonstrated superior precision, with a position error of 1.64 mm and an orientation error of 0.00179 radians when avoiding singularities. These results highlight the potential of QNNs to enhance the precision, efficiency, and performance of robotic arm manipulation. Quantum computing offers advantages including parallelism, quantum entanglement, and quantum annealing, which contribute to the QNNs’ superior performance. Overall, this study represents a practical contribution to robotics and quantum computing, paving the way for future research into applying quantum principles to neural network models for robotics.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105123"},"PeriodicalIF":4.3,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604739","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":"On-policy and Off-policy Q-learning algorithms with policy iteration for two-wheeled inverted pendulum systems","authors":"Ba Quoc Anh Nguyen ,&nbsp;Ngoc Trung Dang ,&nbsp;Thanh Tung Le ,&nbsp;Phuong Nam Dao","doi":"10.1016/j.robot.2025.105111","DOIUrl":"10.1016/j.robot.2025.105111","url":null,"abstract":"<div><div>This article delves into the investigation of On-policy and Off-policy Q-learning algorithms for controlling two-wheeled inverted pendulum (TWIP) robots in situations where knowledge about the dynamic system is uncertain. Both on-policy and off-policy Q-learning algorithms ensure optimal and model-free control by employing a data collection approach without the knowledge of model. The On-policy algorithm performs real-time data collection, continuously gathering data and iteratively calculating a new control policy until it converges to the optimal value. In contrast, the Off-policy algorithm collects data only once and applies it to the system after completing the learning process. To enhance computational efficiency and minimize the amount of data required, the TWIP system is divided into two Sub-systems. These Sub-systems consist of smaller system matrices that can be controlled independently. This division reduces the data collection burden and accelerates the calculation speed of the algorithms. The utilization of Off-policy techniques proves to be advantageous in developing algorithms with data efficiency and achieving higher accuracy. The influence of probing noise on the Q-function is comprehensively considered in both proposed algorithms. By utilizing a single data set and eliminating the influence of noise, the Off-policy techniques enhance algorithm performance. Finally, the article presents simulation results of the TWIP system to validate the effectiveness of the two proposed control schemes.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105111"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523056","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":"HighwayLLM: Decision-making and navigation in highway driving with RL-informed language model","authors":"Mustafa Yildirim,&nbsp;Barkin Dagda,&nbsp;Vinal Asodia,&nbsp;Saber Fallah","doi":"10.1016/j.robot.2025.105114","DOIUrl":"10.1016/j.robot.2025.105114","url":null,"abstract":"<div><div>Autonomous driving is a complex task which requires advanced decision making and control algorithms. Understanding the rationale behind the autonomous vehicles’ decision is crucial to ensure their safe and effective operation on highway driving. This study presents a novel approach, <em>HighwayLLM</em>, which harnesses the reasoning capabilities of large language models (LLMs) to predict the future waypoints for ego-vehicle’s navigation. Our approach also utilizes a pre-trained Reinforcement Learning (RL) model to serve as a high-level planner, making decisions on appropriate meta-level actions. The HighwayLLM combines the output from the RL model and the current state information to make safe, collision-free, and explainable predictions for the next states, thereby constructing a trajectory for the ego-vehicle. Subsequently, a PID-based controller guides the vehicle to the waypoints predicted by the LLM agent. This integration of LLM with RL and PID enhances the decision-making process, provides interpretability for highway autonomous driving and reduces the number of collisions compared to the baseline method.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105114"},"PeriodicalIF":4.3,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523181","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":"Challenges: Strong impact operation robots—motion analysis, transient measurement, and vibration suppression strategy","authors":"Tong Mou ,&nbsp;Xianzhong Chen ,&nbsp;Qingwen Hou ,&nbsp;Jiahao Hua ,&nbsp;Zeping Hu ,&nbsp;Chaoda Xie ,&nbsp;Haisheng Zhong ,&nbsp;Zhikun Qi","doi":"10.1016/j.robot.2025.105112","DOIUrl":"10.1016/j.robot.2025.105112","url":null,"abstract":"<div><div>As industry tends to be much intelligence-oriented, the performance of industrial robots faces increasingly a higher demand. Strong Impact Operation Robots (SIORs), additionally with high efficiency and durability, have been widely applied in industry. However, with a feature of high-speed, non-linear and discontinuous impact and heavy load, SIORs inevitably trigger more complex and intense vibrations during the motion process, which restricts the improvement of the operational accuracy, stability and efficiency of such robots. This paper provides an overview of researches on vibration suppression of SIORs, and divides them into three categories, motion analysis and modeling, vibration sensing of impact transients, and design of vibration suppression strategies for impact transients. Taking the metallurgical furnace front operation robot as an example and combining it with real industrial scenarios, this paper points out the major challenges for SIORs in each category, setting up an accurate dynamic model of impact mechanism in a variable temperature environment, so as to realize vibration transient measurements under high-speed, non-linear and discontinuous impact, and cultivate active and passive vibration suppression techniques and model-data-driven strategies. This paper systematically investigates the complex vibration problem in SIORs, of which the findings are significant for enhancing the accuracy, stability and efficiency of SIORs, providing a solid foundation for future research on the complex vibration issues of robots.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105112"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513654","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":"Exploiting robot abstractions in episodic RL via reward shaping and heuristics","authors":"Roberto Cipollone ,&nbsp;Marco Favorito ,&nbsp;Flavio Maiorana ,&nbsp;Giuseppe De Giacomo ,&nbsp;Luca Iocchi ,&nbsp;Fabio Patrizi","doi":"10.1016/j.robot.2025.105116","DOIUrl":"10.1016/j.robot.2025.105116","url":null,"abstract":"<div><div>One major limitation to the applicability of Reinforcement Learning (RL) to many domains of practical relevance, in particular in robotic applications, is the large number of samples required to learn an optimal policy. To address this problem and improve learning efficiency, we consider a linear hierarchy of abstraction layers of the Markov Decision Process (MDP) underlying the target domain. Each layer is an MDP representing a coarser model of the one immediately below in the hierarchy. In this work, we propose novel techniques to automatically define Reward Shaping and Reward Heuristic functions that are based on the solution obtained at a higher level of abstraction and provide rewards to the finer (possibly the concrete) MDP at the lower level, thus inducing an exploration heuristic that can effectively guide the learning process in the more complex domain. In contrast with other works in Hierarchical RL, our technique imposes fewer requirements on the design of the abstract models and is tolerant to modeling errors, thus making the proposed approach practical. We formally analyze the relationship between the abstract models and the exploration heuristic induced in the lower-level domain, we prove that the method guarantees optimal convergence, and finally demonstrate its effectiveness experimentally in several complex robotic domains.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105116"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549605","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":"A system for docking robotic wheelchair to partially visible table of unknown pose using human input and robotic wheelchair motion","authors":"Neha Priyadarshini Garg,&nbsp;Marcus Leong,&nbsp;Manoj Ramanathan,&nbsp;Wee-Ching Pang,&nbsp;Lei Li,&nbsp;Wei Tech Ang","doi":"10.1016/j.robot.2025.105087","DOIUrl":"10.1016/j.robot.2025.105087","url":null,"abstract":"<div><div>Existing autonomous table docking approaches require large part of table to be visible in order to compute good docking pose for a table with unknown pose. However, in real world settings like cluttered offices and food courts, users often need to initiate docking when the table is only partially visible. This work focuses on the development of a table docking system that enables a wheelchair user to dock to a table with unknown pose, even when the table is partially visible by using human input and the wheelchair motion. An intuitive point-and-click interface is implemented to allow user to initiate docking, by simply clicking on table in the RGB image of the scene. Docking pose is calculated by extracting table edge from the point cloud using the information provided by the user’s click and the streaming RGBD camera images of the scene as the wheelchair moves towards the table. Based on our experiments, accurate table docking can be achieved even when the table is only 20% visible using our approach while the baseline system requires at least 70% of the table to be visible. This makes our system applicable in realistic scenarios. During evaluation with human subjects, all the participants preferred our system over the baseline due to ease of use. Quantitatively, our system more than halved the effort required to initiate autonomous docking as compared to the baseline.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105087"},"PeriodicalIF":4.3,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491092","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":"Coverage Trajectory Planning Problem on 3D Terrains with safety constraints for automated lawn mower: Exact and heuristic approaches","authors":"Hang Zhou,&nbsp;Peng Zhang,&nbsp;Zhaohui Liang,&nbsp;Hangyu Li,&nbsp;Xiaopeng Li","doi":"10.1016/j.robot.2025.105109","DOIUrl":"10.1016/j.robot.2025.105109","url":null,"abstract":"<div><div>Recent technological advancements in automation have attracted increased interest in automated lawn mowers. Developing a safe and efficient trajectory to cover entire terrains is crucial for autonomous mowing. Unlike the simplified indoor environments with flat surfaces commonly assumed in existing literature, lawn maintenance typically occurs in complex outdoor settings characterized by irregular terrains, including obstacles and slopes. These irregularities pose significant safety risks, such as the potential for the mower to tip over. This paper introduces the Coverage Trajectory Planning Problem on 3D Terrains (CTPP-3DT), which involves determining both the path and speed profile for an automated lawn mower to effectively cover a general 3D terrain with varying slopes. The objective of the CTPP-3DT is to minimize the completion time, including the time for turning, which satisfies safety constraints on the robot’s speed and acceleration on various slopes. To address this challenge, we first propose a Mixed-Integer Linear Programming (MILP) model based on a graph expansion method, suitable for solving small-scale instances. For larger instances, we develop a decomposition-based heuristic algorithm using Simulated Annealing. Extensive experiments conducted on benchmark instances demonstrate the effectiveness of our proposed MILP model and heuristic algorithm for small-size and large-size instances. The comparison between the optimized strategy and the conservative strategy highlights the necessity of incorporating safety constraints in trajectory planning, resulting in an average reduction of more than 40% in completion time. Furthermore, sensitivity analyses reveal that technological advancements in mowers, such as increasing the maximum speed and acceleration and reducing turning speed, can significantly reduce the overall completion time. Our code and data are available at <span><span>https://github.com/CATS-Lab/Mower-CTPP-3D</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105109"},"PeriodicalIF":4.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523055","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":"Adaptive coordinated impedance control for dual-arm robot symmetric bimanual tasks","authors":"Yang Zhang","doi":"10.1016/j.robot.2025.105110","DOIUrl":"10.1016/j.robot.2025.105110","url":null,"abstract":"<div><div>This paper proposes an adaptive coordinated impedance control scheme to address the challenges of internal force regulation and external force tracking in symmetric bimanual tasks performed by dual-arm robots. The scheme is developed within the hybrid impedance control framework, a specialized variant of the general impedance control approach. First, the contact force is decomposed using the dynamic model of dual-arm manipulation and integrated into the corresponding control loop for real-time impedance parameter adjustment. Then, based on the dynamic model of the closed-chain system, distinct impedance parameter adaptation strategies are designed for internal and external forces to meet their respective force control requirements during manipulation. By enabling real-time impedance parameter adjustments in response to contact force errors, the scheme effectively mitigates trajectory deviations caused by unknown paths and environmental factors, thereby improving dual-arm manipulation performance. Finally, the effectiveness of the adaptive coordinated control scheme is validated through a Matlab-Adams co-simulation on a dual-arm robot, demonstrating its capability in internal force limitation and external force tracking.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105110"},"PeriodicalIF":4.3,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491090","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":"Time-varying control strategies for quadrotor dynamics with enhanced anti-windup capabilities","authors":"João Madeiras ,&nbsp;Carlos Cardeira ,&nbsp;Paulo Oliveira","doi":"10.1016/j.robot.2025.105107","DOIUrl":"10.1016/j.robot.2025.105107","url":null,"abstract":"<div><div>This paper proposes robust control strategies for position and attitude, incorporating anti-windup mechanisms to address actuator saturation and improve transient performance in quadrotors. The methodology features a robust, continuously differentiable, saturated position feedback law with anti-windup compensation, alongside a robust attitude tracking controller formulated in quaternion representation. This framework is particularly adept at handling constant biases in the moment of inertia and constant disturbances in both position and attitude closed-loop subsystems. A dynamic activation mechanism governs the anti-windup component, reducing overshoot and enhancing performance. Leveraging Matrosov’s Theorem, the proposed control architecture demonstrates robustness against bounded disturbances and ensures almost uniform global asymptotic stability of the full tracking error dynamics. Simulation results confirm the viability and effectiveness of the proposed approach.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"193 ","pages":"Article 105107"},"PeriodicalIF":4.3,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523057","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}