IEEE Transactions on Robotics最新文献_第3页

AQUA-SLAM: Tightly-Coupled Underwater Acoustic-Visual-Inertial SLAM With Sensor Calibration

IF 7.8 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

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 Multi-Speed Dubins Motion Model

IF 7.8 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

引用次数: 0

SLIM: Scalable and Lightweight LiDAR Mapping in Urban Environments

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554400

Zehuan Yu;Zhijian Qiao;Wenyi Liu;Huan Yin;Shaojie Shen

{"title":"SLIM: Scalable and Lightweight LiDAR Mapping in Urban Environments","authors":"Zehuan Yu;Zhijian Qiao;Wenyi Liu;Huan Yin;Shaojie Shen","doi":"10.1109/TRO.2025.3554400","DOIUrl":"10.1109/TRO.2025.3554400","url":null,"abstract":"Light detection and ranging (LiDAR) point cloud maps are extensively utilized on roads for robot navigation due to their high consistency. However, dense point clouds face challenges of high memory consumption and reduced maintainability for long-term operations. In this study, we introduce scalable and lightweight LiDAR mapping (SLIM), a scalable and lightweight mapping system for long-term LiDAR mapping in urban environments. The system begins by parameterizing structural point clouds into lines and planes. These lightweight and structural representations meet the requirements of map merging, pose graph optimization, and bundle adjustment, ensuring incremental management and local consistency. For long-term operations, a map-centric nonlinear factor recovery method is designed to sparsify poses while preserving mapping accuracy. We validate the SLIM system with multisession real-world LiDAR data from classical LiDAR mapping datasets, including KITTI, NCLT, HeLiPR, and M2DGR. The experiments demonstrate its capabilities in mapping accuracy, lightweightness, and scalability. Map reuse is also verified through map-based robot localization. Finally, with multisession LiDAR data, the SLIM system provides a globally consistent map with low memory consumption (<inline-formula><tex-math>$sim$</tex-math></inline-formula> 130 KB/km on KITTI).","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2569-2588"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702801","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

Accelerated Reeds–Shepp and Underspecified Reeds–Shepp Algorithms for Mobile Robot Path Planning

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/TRO.2025.3554406

Ibrahim Ibrahim;Wilm Decré;Jan Swevers

{"title":"Accelerated Reeds–Shepp and Underspecified Reeds–Shepp Algorithms for Mobile Robot Path Planning","authors":"Ibrahim Ibrahim;Wilm Decré;Jan Swevers","doi":"10.1109/TRO.2025.3554406","DOIUrl":"10.1109/TRO.2025.3554406","url":null,"abstract":"In this study, we present a simple and intuitive method for accelerating optimal Reeds–Shepp path computation. Our approach uses geometrical reasoning to analyze the behavior of optimal paths, resulting in a new partitioning of the state space and a further reduction in the minimal set of viable paths. We revisit and reimplement classic methodologies from literature, which lack contemporary open-source implementations, to serve as benchmarks for evaluating our method. In addition, we address the underspecified Reeds–Shepp planning problem where the final orientation is unspecified. We perform exhaustive experiments to validate our solutions. Compared to the modern C++ implementation of the original Reeds–Shepp solution in the Open Motion Planning Library, our method demonstrates a <inline-formula><tex-math>$15times$</tex-math></inline-formula> speedup, while classic methods achieve a <inline-formula><tex-math>$5.79times$</tex-math></inline-formula> speedup. Both approaches exhibit machine-precision differences in path lengths compared to the original solution. We release our proposed C++ implementations for both the accelerated and underspecified Reeds–Shepp problems as open-source code.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2691-2708"},"PeriodicalIF":9.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702797","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

Multi-query Robotic Manipulator Task Sequencing with Gromov-Hausdorff Approximations

IF 7.8 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/tro.2025.3554404

Fouad Sukkar, Jennifer Wakulicz, Ki Myung Brian Lee, Weiming Zhi, Robert Fitch

引用次数: 0

Sensitivity-Aware Model Predictive Control for Robots with Parametric Uncertainty

IF 7.8 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-24 DOI: 10.1109/tro.2025.3554415

Tommaso Belvedere, Marco Cognetti, Giuseppe Oriolo, Paolo Robuffo Giordano

引用次数: 0

A Wearable Isokinetic Training Robot for Enhanced Bedside Knee Rehabilitation 用于增强床旁膝关节康复的可穿戴等速训练机器人

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-18 DOI: 10.1109/TRO.2025.3552332

Yanggang Feng;Xingyu Hu;Yuebing Li;Ke Ma;Jiaxin Ren;Zhihao Zhou;Fuzhen Yuan;Yan Huang;Liu Wang;Qining Wang;Wuxiang Zhang;Xilun Ding

{"title":"A Wearable Isokinetic Training Robot for Enhanced Bedside Knee Rehabilitation","authors":"Yanggang Feng;Xingyu Hu;Yuebing Li;Ke Ma;Jiaxin Ren;Zhihao Zhou;Fuzhen Yuan;Yan Huang;Liu Wang;Qining Wang;Wuxiang Zhang;Xilun Ding","doi":"10.1109/TRO.2025.3552332","DOIUrl":"10.1109/TRO.2025.3552332","url":null,"abstract":"Knee pain is prevalent in over 20% of the population, limiting the mobility of those affected. In turn, isokinetic dynamometers and robots have been used to facilitate rehabilitation for those still capable of ambulation. However, there are at most only a few wearable robots capable of delivering isokinetic training for bedridden patients. Here, we developed a wearable robot that provides bedside isokinetic training by utilizing a variable stiffness actuator and dynamic energy regeneration. The efficacy of this device was validated in a study involving six subjects with debilitating knee injuries. During two courses of rehabilitation over a total of three weeks, the average peak torque, average torque, and average work produced by their affected knees increased significantly by 81.0%, 101.4%, and 117.6%, respectively. Furthermore, the device's energy regeneration features were found capable of extending its operating time to 198 days under normal usage, representing a 57.8% increase over the same device without regeneration. These results suggest potential methodologies for delivering isokinetic joint rehabilitation to bedridden patients in areas with limited infrastructure.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2460-2476"},"PeriodicalIF":9.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661154","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

High Resolution, Large Area Vision-Based Tactile Sensing Based on a Novel Piezoluminescent Skin

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552327

Ruxiang Jiang;Lanhui Fu;Yanan Li;Hareesh Godaba

{"title":"High Resolution, Large Area Vision-Based Tactile Sensing Based on a Novel Piezoluminescent Skin","authors":"Ruxiang Jiang;Lanhui Fu;Yanan Li;Hareesh Godaba","doi":"10.1109/TRO.2025.3552327","DOIUrl":"10.1109/TRO.2025.3552327","url":null,"abstract":"The ability to precisely perceive external physical interactions would enable robots to interact effectively with the environment and humans. While vision-based tactile sensing has improved robotic grippers, it is challenging to realize high resolution vision-based tactile sensing in robot arms due to presence of curved surfaces, difficulty in uniform illumination, and large distance of sensing area from the cameras. In this article, we propose a novel piezoluminescent skin that transduces external applied pressures into changes in light intensity on the other side for viewing by a camera for pressure estimation. By engineering elastomer layers with specific optical properties and integrating a flexible electroluminescent panel as a light source, we develop a compact tactile sensing layer that resolves the layout issues in curved surfaces. We achieved multipoint pressure estimation over an expansive area of 502 cm<sup>2</sup> with high spatial resolution, a two-point discrimination distance of 3 mm horizontally and 5 mm vertically which is comparable to that of human fingers as well as a high localization accuracy (RMSE of 1.92 mm). These promising attributes make this tactile sensing technique suitable for use in robot arms and other applications requiring high resolution tactile information over a large area.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2477-2494"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640774","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

CODEI: Resource-Efficient Task-Driven Codesign of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552347

Dejan Milojevic;Gioele Zardini;Miriam Elser;Andrea Censi;Emilio Frazzoli

{"title":"CODEI: Resource-Efficient Task-Driven Codesign of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles","authors":"Dejan Milojevic;Gioele Zardini;Miriam Elser;Andrea Censi;Emilio Frazzoli","doi":"10.1109/TRO.2025.3552347","DOIUrl":"10.1109/TRO.2025.3552347","url":null,"abstract":"This article discusses the integration challenges and strategies for designing mobile robots, by focusing on the task-driven, optimal selection of hardware and software to balance safety, efficiency, and minimal usage of resources such as costs, energy, computational requirements, and weight. We emphasize the interplay between perception and motion planning in decision-making by introducing the concept of occupancy queries to quantify the perception requirements for sampling-based motion planners. Sensor and algorithm performance are evaluated using false negative rate and false positive rate across various factors such as geometric relationships, object properties, sensor resolution, and environmental conditions. By integrating perception requirements with perception performance, an integer linear programming approach is proposed for efficient sensor and algorithm selection and placement. This forms the basis for a codesign optimization that includes the robot body, motion planner, perception pipeline, and computing unit. We refer to this framework for solving the codesign problem of mobile robots as CODEI, short for codesign of embodied intelligence. A case study on developing an autonomous vehicle for urban scenarios provides actionable information for designers, and shows that complex tasks escalate resource demands, with task performance affecting choices of the autonomy stack. The study demonstrates that resource prioritization influences sensor choice: cameras are preferred for cost-effective and lightweight designs, while lidar sensors are chosen for better energy and computational efficiency.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2727-2748"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640488","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