Robotics and Autonomous Systems最新文献

{"title":"Automatic measurement process for hand–eye calibration based on Archimedean solids pose distribution","authors":"Kaifan Zhong,&nbsp;Nianfeng Wang,&nbsp;Xianmin Zhang","doi":"10.1016/j.robot.2026.105333","DOIUrl":"10.1016/j.robot.2026.105333","url":null,"abstract":"<div><div>Hand–eye calibration is a vital process for determining an unknown transformation between sensors and a robot end frame before applying robot vision. In addition to optimizing the mathematical solution, refining the pose distribution involved in the calibration can improve the calibration accuracy and efficiency. To optimize the pose distribution, the 3-D position distribution of the tool centre point is designed first, and then the final poses are determined considering the current application scenario. In this paper, an automatic pose generation method is proposed to stably output suitable poses in on-site calibration scenes when an arbitrary 3-D position distribution of the tool centre point is input. Based on this, different pose distributions are discussed regarding their effect on the calibration error, and an indicator is presented to evaluate the performance of these distributions before executing a calibration process. Moreover, a special pose distribution formed by an Archimedean solid is presented, and it shows better performance in improving the hand–eye calibration accuracy and efficiency. Both simulation and on-site experiments are carried out to verify the proposed methods and analyse the effect of different distributions on the calibration results.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105333"},"PeriodicalIF":5.2,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940042","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":"Human–robot collaborative control method based on command-weighted fusion strategy for manned legged robot","authors":"Yaojin Fan ,&nbsp;Bo You ,&nbsp;Jiayu Li ,&nbsp;Yufei Liu ,&nbsp;Chen Chen ,&nbsp;Xiaolei Chen ,&nbsp;Liang Ding","doi":"10.1016/j.robot.2025.105323","DOIUrl":"10.1016/j.robot.2025.105323","url":null,"abstract":"<div><div>This paper proposes a human–robot collaborative control method based on command-weighted fusion strategy for manned legged robot, addressing challenges posed by the complex structure of manned legged robots. These challenges affect both the safety of autonomous decision-making algorithms and the complexity of manual control. First, we design an autonomous command optimization method integrating terrain information and cost functions to enhance decision-making in complex terrains. Subsequently, a method for optimizing driving weighting factors is designed, utilizing a prior mechanism and rule knowledge base, while considering the influence of driver reliability and terrain complexity on driving safety and stability. Through analysis of human-machine driving intentions and the autonomous driving weighting factor, a commands weighted fusion strategy for human-machine commands is devised to achieve rational dynamic allocation of driving weighting and command fusion. Finally, validation through a human–robot collaborative control experiment demonstrates that the proposed control strategy effectively leverages the strengths of both human drivers and intelligent systems, yielding satisfactory control performance.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105323"},"PeriodicalIF":5.2,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978322","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 the video quality captured by a surveillance mobile robot","authors":"Adwaith Vijayakumar ,&nbsp;Ishank Juneja ,&nbsp;Leena Vachhani","doi":"10.1016/j.robot.2026.105330","DOIUrl":"10.1016/j.robot.2026.105330","url":null,"abstract":"<div><div>In many robot surveillance applications, the major contributor to the quality degradation of the captured video is the unintended relative motion between the camera and the scene. This unintended motion induces an unintended effect called <em>jitter</em> in the captured video sequence. The evaluation of video quality captured by a mobile robot in surveillance scenarios is often application-specific and is often based on the amount of jitter obtained through feature tracking or camera path reconstruction or intensity patterns obtained across video frames. The contributions in this paper are two folds: development and benchmarking of a novel algorithm for video quality assessment, and jitter-specific recommendations for stabilization approaches. Unlike existing Video Quality Assessment (VQA) scores, the proposed Topology Score (TS) is a non-reference technique that does not involve feature tracking or camera path reconstruction, suitable for mobile robots used for surveillance. We adopt sliding window geometry using persistent homology concept for quantifying the jitter associated with the periodic/quasiperiodic oscillations induced by the moving mobile robots, which in turn gives a VQA score. The experimental results suggest that the trend of the proposed score aligns with the existing rhythm scores that correlate highly with human subjective evaluation, but needs reference video for the assessment. Additionally, we perform a comparative study on various video stabilization algorithms on three categories of robots based on the jitter characteristics: (1) Spherical robot videos with second-order damped oscillations causing low-frequency high-amplitude jitters, (2) Autonomous drone videos with intermittent jitters, and (3) Humanoids mimicked by the casual movements of hand-held video recorder (gait motions have a periodic structure) that contain high-frequency low-amplitude jitters from the recorder’s movement, using the proposed and existing VQA scores. We apply seven different stabilization approaches to the selected robot categories and quantify the tested algorithms’ output quality and resource requirements. Finally, we report the decision matrix based on the robot’s available resources to readily use the state-of-the-art stabilization methods in mobile robot surveillance. Our findings show that the proposed topology score is most suitable for evaluating videos captured by mobile robots in unknown environments due to non-reference assessment associated with periodic/quasiperiodic jitter, and the decision matrix to select a video stabilization algorithm based on the jitter characteristics of mobile robot for the quality improvement of captured video.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105330"},"PeriodicalIF":5.2,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885486","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":"Curriculum-guided deep reinforcement learning with fuzzy rewards for autonomous push-grasp manipulation in cluttered environments","authors":"Chih-Yung Huang ,&nbsp;Adhan Efendi ,&nbsp;Ying-Chun Wang","doi":"10.1016/j.robot.2025.105325","DOIUrl":"10.1016/j.robot.2025.105325","url":null,"abstract":"<div><div>Robotic manipulation in cluttered environments requires robust coordination of pushing and grasping to overcome occlusions, constrained grasp geometries, and uncertain object interactions. This study presents a curriculum-guided deep reinforcement learning framework that jointly redesigns the training distribution, state abstraction, and reward structure for autonomous push–grasp manipulation. A depth-aware grasp potential module constructs a geometric affordance map that prioritizes feasible top-layer grasp opportunities, guiding the agent toward collision-free rearrangement behaviors. A fuzzy logic–based reward mechanism integrates changes in graspable area and grasp Q-values into a continuous shaping signal, addressing sparse feedback and stabilizing learning. A stage-wise curriculum with proportion-controlled difficulty progression gradually increases clutter density and object difficulty, enabling progressive acquisition of coordinated push–grasp skills. Extensive evaluations across randomized clutter, structured challenge scenarios, and real-world experiments on previously unseen and semi-transparent objects show that the proposed framework consistently outperforms VPG-based and grasp-quality baselines in grasp success and action efficiency. These results demonstrate the effectiveness of coupling curriculum design, depth-aware grasp prioritization, and fuzzy reward shaping for robust manipulation in complex, cluttered settings.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105325"},"PeriodicalIF":5.2,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037689","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":"Reliable Nonsingularity Adaptive fixed-time sliding mode control under input saturation for an uncertain robotic manipulator","authors":"Van Tinh Nguyen ,&nbsp;Thanh Tung Bui ,&nbsp;Hai Yen Pham ,&nbsp;Ngoc Thanh Pham ,&nbsp;Dang-Khoa Nguyen ,&nbsp;Saleh Mobayen","doi":"10.1016/j.robot.2025.105326","DOIUrl":"10.1016/j.robot.2025.105326","url":null,"abstract":"<div><div>This paper proposes a novel reliable terminal sliding mode control (TSMC) scheme for an uncertain robotic manipulator that is susceptible to parameter uncertainties, external disturbances, and input saturation. The suggested approach guarantees constant time tracking errors and non-singular convergence regardless of initial conditions by combining the classic pole placement technique with a well-designed sliding manifold. Both the unknown nonlinear dynamics and uncertainties are approximated using a radial basis function neural network (RBFNN), and the effects of input saturation are lessened by an appropriate solution. The system states converge to a small neighborhood of the origin in a limited amount of time, according to theoretical analysis based on Lyapunov stability lemmas and constant time stability. Simulation results confirm the superior performance of the proposed approach compared to existing methods, showing better accuracy, reduced chatter, and saved energy. This control strategy offers a practical and effective solution for high-precision path tracking in robotic systems operating in challenging environments.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105326"},"PeriodicalIF":5.2,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940045","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":"The rapid rise of soft robotics in surgical operations: Trends, challenges, and future directions","authors":"Babatunde Olamide Omiyale ,&nbsp;Olamide Femi Akinsola ,&nbsp;Muhammad Awais Ashraf ,&nbsp;Niyi Gideon Olaiya ,&nbsp;Akinola Ogbeyemi ,&nbsp;Wenjun Chris Zhang","doi":"10.1016/j.robot.2025.105324","DOIUrl":"10.1016/j.robot.2025.105324","url":null,"abstract":"<div><div>This paper investigates the transformative impact of soft robotics on surgical operations, particularly in the development of next-generation minimally invasive techniques. Conventional surgical procedures are often influenced by various factors, such as patient positioning, the precision of surgical instruments, the surgeon’s experience, and physical conditions. These factors can make it challenging to accurately execute predetermined surgical plans, which can inevitably reduce surgical precision and safety. To address these challenges, soft robotic systems that mimic the flexibility and adaptability of biological tissues provide significant advantages over conventional rigid tools. These advantages include enhanced dexterity, reduced tissue trauma, and improved patient outcomes. Soft robots are made from compliant materials (e.g., silicone, hydrogels), which make them gentler on delicate tissues and organs. They can navigate tight or sensitive areas (e.g., the brain, heart, abdomen), allow for smaller incisions, minimize blood loss, reduce the risk of infection, and minimize recovery time, scarring, and human error caused by tremors or physical strain. This review examines recent advancements in soft robotics, clinical applications, addresses technological challenges, and identifies future directions for integrating soft robotics into mainstream surgical practice.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105324"},"PeriodicalIF":5.2,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978235","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 Euclidean distance field properties for fast and safe 3D planning with a modified Lazy Theta*","authors":"Jose A. Cobano,&nbsp;L. Merino,&nbsp;F. Caballero","doi":"10.1016/j.robot.2025.105317","DOIUrl":"10.1016/j.robot.2025.105317","url":null,"abstract":"<div><div>This paper presents the FS-Planner, a fast graph-search planner based on a modified Lazy Theta* algorithm that exploits the analytical properties of Euclidean Distance Fields (EDFs). We introduce a new cost function that integrates an EDF-based term proven to satisfy the triangle inequality, enabling efficient parent selection and reducing computation time while generating safe paths with smaller heading variations. We also derive an analytic approximation of the EDF integral along a segment and analyse the influence of the line-of-sight limit on the approximation error, motivating the use of a bounded visibility range. Furthermore, we propose a gradient-based neighbour-selection mechanism that decreases the number of explored nodes and improves computational performance without degrading safety or path quality. The FS-Planner produces safe paths with small heading changes without requiring the use of post-processing methods. Extensive experiments and comparisons in challenging 3D indoor simulation environments, complemented by tests in real-world outdoor environments, are used to evaluate and validate the FS-Planner. The results show consistent improvements in computation time, exploration efficiency, safety, and smoothness in a geometric sense compared with baseline heuristic planners, while maintaining sub-optimality within acceptable bounds. Finally, the proposed EDF-based cost formulation is orthogonal to the underlying search method and can be incorporated into other planning paradigms.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105317"},"PeriodicalIF":5.2,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145940044","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":"MirrorNet: Hallucinating 2.5D depth images for efficient 3D scene reconstruction","authors":"Rafał Staszak,&nbsp;Bartlomiej Kulecki,&nbsp;Marek Kraft,&nbsp;Dominik Belter","doi":"10.1016/j.robot.2025.105321","DOIUrl":"10.1016/j.robot.2025.105321","url":null,"abstract":"<div><div>Robots face challenges in perceiving new scenes, particularly when registering objects from a single perspective, resulting in incomplete shape information about objects. Partial object models negatively influence the performance of grasping methods. To address this, robots can scan the scene from various perspectives or employ methods to directly fill in unknown regions. This research reexamines scene reconstruction typically formulated in 3D space, proposing a novel formulation in 2D image space for robots with RGB-D cameras. We introduce a method that generates a depth image from a virtual camera pose located on the opposite position of the reconstructed object. The article demonstrates that the convolutional neural network can be trained for accurate depth image generation and subsequent 3D scene reconstruction from a single viewpoint. We show that the proposed approach is computationally efficient and accurate when compared to methods that operate directly in 3D space. Furthermore, we illustrate the application of this model in enhancing grasping method success rates.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105321"},"PeriodicalIF":5.2,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885479","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 flexibility and dexterity in robotic endoscopy via a 6-DOF parallel mechanism and eye-gaze-assisted field-of-view control","authors":"Mengtang Li ,&nbsp;Shen Zhao ,&nbsp;Shuai Wang ,&nbsp;Fanmao Liu","doi":"10.1016/j.robot.2025.105322","DOIUrl":"10.1016/j.robot.2025.105322","url":null,"abstract":"<div><div>In conventional minimally invasive surgery, an assistant manually steers the endoscope based on the surgeon’s verbal commands, but fatigue and tremor can degrade field-of-view (FOV) stability and efficiency. Robotic endoscopes address this limitation through automated FOV adjustment via image-based visual servoing, ensuring smooth and stable visualization. However, most robotic implementations mount rigid straight-rod endoscopes on external serial arms, limiting dexterity and complicating remote-center-of-motion (RCM) control. Moreover, many automated FOV methods track surgical-tool tips without representing the surgeon’s intention. This work therefore presents a compact 6-DOF parallel endoscopic mechanism that improves flexibility and dexterity while simplifying RCM constraint satisfaction, together with an eye-gaze-assisted multi-tool tracking controller that dynamically weights tools according to surgeon attention. Simulations and experiments across diverse scenarios demonstrate FOV stabilization within 2 s, mean image-space tracking error <span><math><mo>&lt;</mo></math></span> 20 pixels, eye hand error <span><math><mo>&lt;</mo></math></span> 3°, and at least a 30% reduction in unnecessary FOV adjustments. Supplementary video is available.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105322"},"PeriodicalIF":5.2,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885484","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":"Reference-guided image inpainting via progressive feature interaction and reconstruction for mobile robots with binocular cameras","authors":"Jingyi Liu ,&nbsp;Hengyu Li ,&nbsp;Hang Liu ,&nbsp;Shaorong Xie ,&nbsp;Jun Luo","doi":"10.1016/j.robot.2025.105320","DOIUrl":"10.1016/j.robot.2025.105320","url":null,"abstract":"<div><div>Image inpainting is a critical technique for recovering missing information caused by camera soiling on mobile robots. However, most existing learning-based methods still struggle to handle damaged images with complex semantic environments and diverse hole patterns, primarily because of the insufficient acquisition and inadequate fusion of scene-consistent prior cues for damaged images. To address this limitation, we propose a novel reference-guided image inpainting network (<span><math><mrow><msup><mrow><mi>RGI</mi></mrow><mrow><mn>2</mn></mrow></msup><mi>N</mi></mrow></math></span>) for mobile robots equipped with binocular cameras, which employs adjacent camera images as inpainting guidance and fuses its prior information via progressive feature interaction to reconstruct damaged regions. Specifically, a back-projection-based feature interaction module (FIM) is proposed to align the features of the reference and damaged images, thereby capturing the contextual information of the reference image for inpainting. Additionally, a content reconstruction module (CRM) based on residual learning and channel attention is presented to selectively aggregate interactive features for reconstructing missing details. Building upon these two modules, we further devise a progressive feature interaction and reconstruction module (PFIRM) that organizes multiple FIM-CRM pairs into a stepwise structure, enabling the progressive fusion of multiscale contextual information derived from both the damaged and reference images. Moreover, a feature refinement module (FRM) is developed to interact with low-level fine-grained features and refine the reconstructed details. Extensive evaluations conducted on the public ETHZ dataset and our self-built MII dataset demonstrate that <span><math><mrow><msup><mrow><mi>RGI</mi></mrow><mrow><mn>2</mn></mrow></msup><mi>N</mi></mrow></math></span> outperforms other state-of-the-art approaches and produces high-quality inpainting results on real soiled data.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"198 ","pages":"Article 105320"},"PeriodicalIF":5.2,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842778","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}