IEEE Transactions on Robotics最新文献_第10页

A Learning-Based Method for Computing Self-Motion Manifolds of Redundant Robots for Real-Time Fault-Tolerant Motion Planning 基于学习的冗余机器人自运动流形计算方法及实时容错运动规划

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-04-09 DOI: 10.1109/TRO.2025.3559404

Charles L. Clark;Biyun Xie

{"title":"A Learning-Based Method for Computing Self-Motion Manifolds of Redundant Robots for Real-Time Fault-Tolerant Motion Planning","authors":"Charles L. Clark;Biyun Xie","doi":"10.1109/TRO.2025.3559404","DOIUrl":"10.1109/TRO.2025.3559404","url":null,"abstract":"The focus of this research is to develop a learning-based method that computes self-motion manifolds (SMMs) efficiently and accurately to enable real-time global fault-tolerant motion planning. The proposed method first develops a learnable, closed-form representation of SMMs based on Fourier series. A cellular automaton is then applied to cluster workspace locations having the same number of SMMs and group SMMs with similar shape by homotopy classes, such that the SMMs of each homotopy class can be accurately learned by a neural network. To approximate the SMMs of an arbitrary workspace location, a neural network is first trained to predict the set of homotopy classes belonging to this workspace location. For each set of homotopy classes, another neural network is trained to approximate the Fourier series coefficients of the SMMs, and the joint configurations along the SMMs can be retrieved using the inverse Fourier transform. The proposed method is validated on planar 3R positioning, spatial 4R positioning, and spatial 7R positioning and orienting robots, using 10 000 randomly sampled workspace locations each. The results show that the proposed method can approximate SMMs with high accuracy and is much faster than the traditionally used nullspace projection method, a sampling-based method, and a grid-based method. The performance of the proposed method in real-time fault-tolerant motion planning applications is also demonstrated using the simulation of the spatial 7R robot and physical experiments on a planar 3R robot. Due to the computational efficiency of the proposed method, both robots are able to quickly plan trajectories which maximize the likelihood of task completion after the failure of one arbitrary joint.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2879-2893"},"PeriodicalIF":9.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NeuPAN: Direct Point Robot Navigation With End-to-End Model-Based Learning 基于端到端模型学习的直接点机器人导航

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-26 DOI: 10.1109/TRO.2025.3554252

Ruihua Han;Shuai Wang;Shuaijun Wang;Zeqing Zhang;Jianjun Chen;Shijie Lin;Chengyang Li;Chengzhong Xu;Yonina C. Eldar;Qi Hao;Jia Pan

{"title":"NeuPAN: Direct Point Robot Navigation With End-to-End Model-Based Learning","authors":"Ruihua Han;Shuai Wang;Shuaijun Wang;Zeqing Zhang;Jianjun Chen;Shijie Lin;Chengyang Li;Chengzhong Xu;Yonina C. Eldar;Qi Hao;Jia Pan","doi":"10.1109/TRO.2025.3554252","DOIUrl":"10.1109/TRO.2025.3554252","url":null,"abstract":"Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision avoidance. This article presents neural proximal alternating-minimization network (NeuPAN): a real-time, highly accurate, map-free, easy-to-deploy, and environment-invariant robot motion planner. Leveraging a tightly coupled perception-to-control framework, NeuPAN has two key innovations compared to existing approaches: first, it directly maps raw point cloud data to a latent distance feature space for collision-free motion generation, avoiding error propagation from the perception to control pipeline; second, it is interpretable from an end-to-end model-based learning perspective. The crux of NeuPAN is solving an end-to-end mathematical model with numerous point-level constraints using a plug-and-play proximal alternating-minimization network, incorporating neurons in the loop. This allows NeuPAN to generate real-time, physically interpretable motions. It seamlessly integrates data and knowledge engines, and its network parameters can be fine-tuned via backpropagation. We evaluate NeuPAN on a ground mobile robot, a wheel-legged robot, and an autonomous vehicle, in extensive simulated and real-world environments. Results demonstrate that NeuPAN outperforms existing baselines in terms of accuracy, efficiency, robustness, and generalization capabilities across various environments, including the cluttered sandbox, office, corridor, and parking lot. We show that NeuPAN works well in unknown and unstructured environments with arbitrarily shaped objects, transforming impassable paths into passable ones.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2804-2824"},"PeriodicalIF":9.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143723294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wrench Control of Dual-Arm Robot on Flexible Base With Supporting Contact Surface 支撑接触面柔性基座上双臂机器人的扳手控制

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-26 DOI: 10.1109/TRO.2025.3554411

Jeongseob Lee;Doyoon Kong;Hojun Cha;Jeongmin Lee;Dongseok Ryu;Hocheol Shin;Dongjun Lee

{"title":"Wrench Control of Dual-Arm Robot on Flexible Base With Supporting Contact Surface","authors":"Jeongseob Lee;Doyoon Kong;Hojun Cha;Jeongmin Lee;Dongseok Ryu;Hocheol Shin;Dongjun Lee","doi":"10.1109/TRO.2025.3554411","DOIUrl":"10.1109/TRO.2025.3554411","url":null,"abstract":"We propose a novel high-force/high-precision interaction control framework of a dual-arm robot system on a flexible base, with one arm holding, or making contact with, a supporting surface, while the other arm can exert any arbitrary wrench in a certain polytope through a desired pose against environments or objects. Our proposed framework can achieve high-force/precision tasks by utilizing the supporting surface just as we humans do while taking into account various important constraints (e.g., system stability, joint angle/torque limits, friction-cone constraint, etc.) and the passive compliance of the flexible base. We first design the control as a combination of: 1) nominal control; 2) active stiffness control; and 3) feedback wrench control. We then sequentially perform optimizations of the nominal configuration (and its related wrenches) and the active stiffness control gain. We also design the proportional–integral type feedback wrench control to improve the robustness and precision of the control. The key theoretical enabler for our framework is a novel stiffness analysis of the dual-arm system with flexibility, which, when combined with certain constraints, provides some peculiar relations, that can effectively be used to significantly simplify the optimization problem-solving and to facilitate the feedback wrench control design by manifesting the compliance relation at the interaction port. The efficacy of the theory is then validated and demonstrated through simulations and experiments.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2625-2644"},"PeriodicalIF":9.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10938340","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143723293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Primitive-Swarm: An Ultra-Lightweight and Scalable Planner for Large-Scale Aerial Swarms 原始蜂群：一个超轻量级和可扩展的大规模空中蜂群规划器

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-26 DOI: 10.1109/TRO.2025.3573667

Jialiang Hou;Xin Zhou;Neng Pan;Ang Li;Yuxiang Guan;Chao Xu;Zhongxue Gan;Fei Gao

{"title":"Primitive-Swarm: An Ultra-Lightweight and Scalable Planner for Large-Scale Aerial Swarms","authors":"Jialiang Hou;Xin Zhou;Neng Pan;Ang Li;Yuxiang Guan;Chao Xu;Zhongxue Gan;Fei Gao","doi":"10.1109/TRO.2025.3573667","DOIUrl":"10.1109/TRO.2025.3573667","url":null,"abstract":"Achieving large-scale aerial swarms is challenging due to the inherent contradictions in balancing computational efficiency and scalability. This article introduces <italic>primitive-swarm</i>, an ultra-lightweight and scalable planner designed specifically for large-scale autonomous aerial swarms. The proposed approach adopts a decentralized and asynchronous replanning strategy. Within it is a novel motion primitive library consisting of time-optimal and dynamically feasible trajectories. They are generated utilizing a novel time-optimal path parameterization algorithm based on reachability analysis. Then, a rapid collision checking mechanism is developed by associating the motion primitives with the discrete surrounding space according to conflicts. By considering both spatial and temporal conflicts, the mechanism handles robot-obstacle and robot–robot collisions simultaneously. Then, during a replanning process, each robot selects the safe and minimum cost trajectory from the library based on user-defined requirements. Both the time-optimal motion primitive library and the occupancy information are computed offline, turning a time-consuming optimization problem into a linear-complexity selection problem. This enables the planner to comprehensively explore the nonconvex, discontinuous 3-D safe space filled with numerous obstacles and robots, effectively identifying the best hidden path. Benchmark comparisons demonstrate that our method achieves the shortest flight time and traveled distance with a computation time of less than 1 ms in dense environments. Super large-scale swarm simulations, involving up to 1000 robots, running in real time, verify the scalability of our method. Real-world experiments validate the feasibility and robustness of our approach. The code will be released to foster community collaboration.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"3629-3648"},"PeriodicalIF":9.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

General Place Recognition Survey: Toward Real-World Autonomy 一般地点识别调查：走向现实世界的自主性

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3550771

Peng Yin;Jianhao Jiao;Shiqi Zhao;Lingyun Xu;Guoquan Huang;Howie Choset;Sebastian Scherer;Jianda Han

{"title":"General Place Recognition Survey: Toward Real-World Autonomy","authors":"Peng Yin;Jianhao Jiao;Shiqi Zhao;Lingyun Xu;Guoquan Huang;Howie Choset;Sebastian Scherer;Jianda Han","doi":"10.1109/TRO.2025.3550771","DOIUrl":"10.1109/TRO.2025.3550771","url":null,"abstract":"In the realm of robotics, the quest for achieving real-world autonomy, capable of executing large-scale and long-term operations, has positioned place recognition (PR) as a cornerstone technology. Despite the PR community's remarkable strides over the past two decades, garnering attention from fields like computer vision and robotics, the development of PR methods that sufficiently support real-world robotic systems remains a challenge. This article aims to bridge this gap by highlighting the crucial role of PR within the framework of simultaneous localization and mapping 2.0. This new phase in robotic navigation calls for scalable, adaptable, and efficient PR solutions by integrating advanced artificial intelligence technologies. For this goal, we provide a comprehensive review of the current state-of-the-art advancements in PR, alongside the remaining challenges, and underscore its broad applications in robotics. This article begins with an exploration of PR's formulation and key research challenges. We extensively review literature, focusing on related methods on place representation and solutions to various PR challenges. Applications showcasing PR's potential in robotics, key PR datasets, and open-source libraries are discussed.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"3019-3038"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ProxDDP: Proximal Constrained Trajectory Optimization PROXDDP：近端约束轨迹优化

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554437

Wilson Jallet;Antoine Bambade;Etienne Arlaud;Sarah El-Kazdadi;Nicolas Mansard;Justin Carpentier

{"title":"ProxDDP: Proximal Constrained Trajectory Optimization","authors":"Wilson Jallet;Antoine Bambade;Etienne Arlaud;Sarah El-Kazdadi;Nicolas Mansard;Justin Carpentier","doi":"10.1109/TRO.2025.3554437","DOIUrl":"10.1109/TRO.2025.3554437","url":null,"abstract":"Trajectory optimization has been a popular choice for motion generation and control in robotics for at least a decade. Several numerical approaches have exhibited the required speed to enable online computation of trajectories for real-time of various systems, including complex robots. Many of these said are based on the differential dynamic programming (DDP) algorithm—initially designed for unconstrained trajectory optimization problems—and its variants, which are relatively easy to implement and provide good runtime performance. However, several problems in robot control call for using constrained formulations (e.g., torque limits, obstacle avoidance), from which several difficulties arise when trying to adapt DDP-type methods: numerical stability, computational efficiency, and constraint satisfaction. In this article, we leverage proximal methods for constrained optimization and introduce a DDP-type method for fast, constrained trajectory optimization suited for model-predictive control (MPC) applications with easy warm-starting. Compared to earlier solvers, our approach effectively manages hard constraints without warm-start limitations and exhibits good convergence behavior. We provide a complete implementation as part of an open-source and flexible C++ trajectory optimization library called <sc>aligator</small>. These algorithmic contributions are validated through several trajectory planning scenarios from the robotics literature and the real-time whole-body MPC of a quadruped robot.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2605-2624"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simultaneous Trajectory Optimization and Contact Selection for Contact-Rich Manipulation With High-Fidelity Geometry 高保真几何多接触操作的同步轨迹优化和接触选择

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554380

Mengchao Zhang;Devesh K. Jha;Arvind U. Raghunathan;Kris Hauser

{"title":"Simultaneous Trajectory Optimization and Contact Selection for Contact-Rich Manipulation With High-Fidelity Geometry","authors":"Mengchao Zhang;Devesh K. Jha;Arvind U. Raghunathan;Kris Hauser","doi":"10.1109/TRO.2025.3554380","DOIUrl":"10.1109/TRO.2025.3554380","url":null,"abstract":"Contact-implicit trajectory optimization (CITO) is an effective method to plan complex trajectories for various contact-rich systems including manipulation and locomotion. CITO formulates a mathematical program with complementarity constraints (MPCC) that enforces that contact forces must be zero when points are not in contact. However, MPCC solve times increase steeply with the number of allowable points of contact, which limits CITO's applicability to problems in which only a few, simple geometries are allowed us to make contact. This article introduces simultaneous trajectory optimization and contact selection (STOCS), as an extension of CITO that overcomes this limitation. The innovation of STOCS is to identify salient contact points and times inside the iterative trajectory optimization process. This effectively reduces the number of variables and constraints in each MPCC invocation. The STOCS framework, instantiated with key contact identification subroutines, renders the optimization of manipulation trajectories computationally tractable even for high-fidelity geometries consisting of tens of thousands of vertices.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2677-2690"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AQUA-SLAM: Tightly Coupled Underwater Acoustic-Visual-Inertial SLAM With Sensor Calibration AQUA-SLAM：带传感器标定的紧密耦合水声-视觉-惯性SLAM

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554396

Shida Xu;Kaicheng Zhang;Sen Wang

引用次数: 0

Linearized Virtual Energy Tank for Passivity-Based Bilateral Teleoperation Using Linear MPC 基于线性MPC的双侧无源遥操作线性化虚拟能量罐

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554447

Nicola Piccinelli;Riccardo Muradore

引用次数: 0

Generalized Multispeed Dubins Motion Model 广义多速Dubins运动模型

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554436

James P. Wilson;Shalabh Gupta;Thomas A. Wettergren

{"title":"Generalized Multispeed Dubins Motion Model","authors":"James P. Wilson;Shalabh Gupta;Thomas A. Wettergren","doi":"10.1109/TRO.2025.3554436","DOIUrl":"10.1109/TRO.2025.3554436","url":null,"abstract":"The article develops a novel motion model, called generalized multispeed Dubins motion model (GMDM), which extends the Dubins model by considering multiple speeds. While the Dubins model produces time-optimal paths under a constant-speed constraint, these paths could be suboptimal if this constraint is relaxed to include multiple speeds. This is because a constant speed results in a large minimum turning radius, thus producing paths with longer maneuvers and larger travel times. In contrast, multispeed relaxation allows for slower speed sharp turns, thus producing more direct paths with shorter maneuvers and smaller travel times. Furthermore, the inability of the Dubins model to reduce speed could result in fast maneuvers near obstacles, thus producing paths with high collision risks. In this regard, GMDM provides the motion planners the ability to jointly optimize time and risk by allowing the change of speed along the path. GMDM is built upon the six Dubins path types considering the change of speed on path segments. It is theoretically established that GMDM provides full reachability of the configuration space for any speed selections. Furthermore, it is shown that the Dubins model is a specific case of GMDM for constant speeds. The solutions of GMDM are analytical and suitable for real-time applications. The performance of GMDM in terms of solution quality (i.e., time/time-risk cost) and computation time is comparatively evaluated against the existing motion models in obstacle-free as well as obstacle-rich environments via extensive Monte Carlo simulations. The results show that in obstacle-free environments, GMDM produces near time-optimal paths with significantly lower travel times than the Dubins model while having similar computation times. In obstacle-rich environments, GMDM produces time-risk optimized paths with substantially lower collision risks.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2861-2878"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0