arXiv - CS - Robotics最新文献_第9页

Multi-Robot Coordination Induced in Hazardous Environments through an Adversarial Graph-Traversal Game 通过对抗性图遍历博弈诱导危险环境中的多机器人协调

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08222

James Berneburg, Xuan Wang, Xuesu Xiao, Daigo Shishika

引用次数: 0

Relevance for Human Robot Collaboration 与人机协作的相关性

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.07753

Xiaotong Zhang, Dingcheng Huang, Kamal Youcef-Toumi

{"title":"Relevance for Human Robot Collaboration","authors":"Xiaotong Zhang, Dingcheng Huang, Kamal Youcef-Toumi","doi":"arxiv-2409.07753","DOIUrl":"https://doi.org/arxiv-2409.07753","url":null,"abstract":"Effective human-robot collaboration (HRC) requires the robots to possess\u0000human-like intelligence. Inspired by the human's cognitive ability to\u0000selectively process and filter elements in complex environments, this paper\u0000introduces a novel concept and scene-understanding approach termed `relevance.'\u0000It identifies relevant components in a scene. To accurately and efficiently\u0000quantify relevance, we developed an event-based framework that selectively\u0000triggers relevance determination, along with a probabilistic methodology built\u0000on a structured scene representation. Simulation results demonstrate that the\u0000relevance framework and methodology accurately predict the relevance of a\u0000general HRC setup, achieving a precision of 0.99 and a recall of 0.94.\u0000Relevance can be broadly applied to several areas in HRC to improve task\u0000planning time by 79.56% compared with pure planning for a cereal task, reduce\u0000perception latency by up to 26.53% for an object detector, improve HRC safety\u0000by up to 13.50% and reduce the number of inquiries for HRC by 75.36%. A\u0000real-world demonstration showcases the relevance framework's ability to\u0000intelligently assist humans in everyday tasks.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

iKalibr-RGBD: Partially-Specialized Target-Free Visual-Inertial Spatiotemporal Calibration For RGBDs via Continuous-Time Velocity Estimation iKalibr-RGBD：通过连续时间速度估计对 RGBD 进行部分专用的无目标视觉惯性时空校准

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07116

Shuolong Chen, Xingxing Li, Shengyu Li, Yuxuan Zhou

{"title":"iKalibr-RGBD: Partially-Specialized Target-Free Visual-Inertial Spatiotemporal Calibration For RGBDs via Continuous-Time Velocity Estimation","authors":"Shuolong Chen, Xingxing Li, Shengyu Li, Yuxuan Zhou","doi":"arxiv-2409.07116","DOIUrl":"https://doi.org/arxiv-2409.07116","url":null,"abstract":"Visual-inertial systems have been widely studied and applied in the last two\u0000decades, mainly due to their low cost and power consumption, small footprint,\u0000and high availability. Such a trend simultaneously leads to a large amount of\u0000visual-inertial calibration methods being presented, as accurate spatiotemporal\u0000parameters between sensors are a prerequisite for visual-inertial fusion. In\u0000our previous work, i.e., iKalibr, a continuous-time-based visual-inertial\u0000calibration method was proposed as a part of one-shot multi-sensor resilient\u0000spatiotemporal calibration. While requiring no artificial target brings\u0000considerable convenience, computationally expensive pose estimation is demanded\u0000in initialization and batch optimization, limiting its availability.\u0000Fortunately, this could be vastly improved for the RGBDs with additional depth\u0000information, by employing mapping-free ego-velocity estimation instead of\u0000mapping-based pose estimation. In this paper, we present the continuous-time\u0000ego-velocity estimation-based RGBD-inertial spatiotemporal calibration, termed\u0000as iKalibr-RGBD, which is also targetless but computationally efficient. The\u0000general pipeline of iKalibr-RGBD is inherited from iKalibr, composed of a\u0000rigorous initialization procedure and several continuous-time batch\u0000optimizations. The implementation of iKalibr-RGBD is open-sourced at\u0000(https://github.com/Unsigned-Long/iKalibr) to benefit the research community.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Perceptive Pedipulation with Local Obstacle Avoidance 具有局部障碍物规避功能的感知脚踏装置

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07195

Jonas Stolle, Philip Arm, Mayank Mittal, Marco Hutter

引用次数: 0

FaVoR: Features via Voxel Rendering for Camera Relocalization FaVoR：通过体素渲染实现摄像机重定位的功能

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07571

Vincenzo Polizzi, Marco Cannici, Davide Scaramuzza, Jonathan Kelly

{"title":"FaVoR: Features via Voxel Rendering for Camera Relocalization","authors":"Vincenzo Polizzi, Marco Cannici, Davide Scaramuzza, Jonathan Kelly","doi":"arxiv-2409.07571","DOIUrl":"https://doi.org/arxiv-2409.07571","url":null,"abstract":"Camera relocalization methods range from dense image alignment to direct\u0000camera pose regression from a query image. Among these, sparse feature matching\u0000stands out as an efficient, versatile, and generally lightweight approach with\u0000numerous applications. However, feature-based methods often struggle with\u0000significant viewpoint and appearance changes, leading to matching failures and\u0000inaccurate pose estimates. To overcome this limitation, we propose a novel\u0000approach that leverages a globally sparse yet locally dense 3D representation\u0000of 2D features. By tracking and triangulating landmarks over a sequence of\u0000frames, we construct a sparse voxel map optimized to render image patch\u0000descriptors observed during tracking. Given an initial pose estimate, we first\u0000synthesize descriptors from the voxels using volumetric rendering and then\u0000perform feature matching to estimate the camera pose. This methodology enables\u0000the generation of descriptors for unseen views, enhancing robustness to view\u0000changes. We extensively evaluate our method on the 7-Scenes and Cambridge\u0000Landmarks datasets. Our results show that our method significantly outperforms\u0000existing state-of-the-art feature representation techniques in indoor\u0000environments, achieving up to a 39% improvement in median translation error.\u0000Additionally, our approach yields comparable results to other methods for\u0000outdoor scenarios while maintaining lower memory and computational costs.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enabling Shared-Control for A Riding Ballbot System 实现骑行球机器人系统的共享控制

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07013

Yu Chen, Mahshid Mansouri, Chenzhang Xiao, Ze Wang, Elizabeth T. Hsiao-Wecksler, William R. Norris

{"title":"Enabling Shared-Control for A Riding Ballbot System","authors":"Yu Chen, Mahshid Mansouri, Chenzhang Xiao, Ze Wang, Elizabeth T. Hsiao-Wecksler, William R. Norris","doi":"arxiv-2409.07013","DOIUrl":"https://doi.org/arxiv-2409.07013","url":null,"abstract":"This study introduces a shared-control approach for collision avoidance in a\u0000self-balancing riding ballbot, called PURE, marked by its dynamic stability,\u0000omnidirectional movement, and hands-free interface. Integrated with a sensor\u0000array and a novel Passive Artificial Potential Field (PAPF) method, PURE\u0000provides intuitive navigation with deceleration assistance and haptic/audio\u0000feedback, effectively mitigating collision risks. This approach addresses the\u0000limitations of traditional APF methods, such as control oscillations and\u0000unnecessary speed reduction in challenging scenarios. A human-robot interaction\u0000experiment, with 20 manual wheelchair users and able-bodied individuals, was\u0000conducted to evaluate the performance of indoor navigation and obstacle\u0000avoidance with the proposed shared-control algorithm. Results indicated that\u0000shared-control significantly reduced collisions and cognitive load without\u0000affecting travel speed, offering intuitive and safe operation. These findings\u0000highlight the shared-control system's suitability for enhancing collision\u0000avoidance in self-balancing mobility devices, a relatively unexplored area in\u0000assistive mobility research.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Invariant filtering for wheeled vehicle localization with unknown wheel radius and unknown GNSS lever arm 未知车轮半径和未知全球导航卫星系统杠杆臂的轮式车辆定位不变滤波技术

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07050

Paul ChauchatAMU SCI, AMU, LIS, DIAPRO, Silvère BonnabelCAOR, Axel Barrau

引用次数: 0

Dynamic Fairness Perceptions in Human-Robot Interaction 人机交互中的动态公平感知

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07560

Houston Claure, Kate Candon, Inyoung Shin, Marynel Vázquez

{"title":"Dynamic Fairness Perceptions in Human-Robot Interaction","authors":"Houston Claure, Kate Candon, Inyoung Shin, Marynel Vázquez","doi":"arxiv-2409.07560","DOIUrl":"https://doi.org/arxiv-2409.07560","url":null,"abstract":"People deeply care about how fairly they are treated by robots. The\u0000established paradigm for probing fairness in Human-Robot Interaction (HRI)\u0000involves measuring the perception of the fairness of a robot at the conclusion\u0000of an interaction. However, such an approach is limited as interactions vary\u0000over time, potentially causing changes in fairness perceptions as well. To\u0000validate this idea, we conducted a 2x2 user study with a mixed design (N=40)\u0000where we investigated two factors: the timing of unfair robot actions (early or\u0000late in an interaction) and the beneficiary of those actions (either another\u0000robot or the participant). Our results show that fairness judgments are not\u0000static. They can shift based on the timing of unfair robot actions. Further, we\u0000explored using perceptions of three key factors (reduced welfare, conduct, and\u0000moral transgression) proposed by a Fairness Theory from Organizational Justice\u0000to predict momentary perceptions of fairness in our study. Interestingly, we\u0000found that the reduced welfare and moral transgression factors were better\u0000predictors than all factors together. Our findings reinforce the idea that\u0000unfair robot behavior can shape perceptions of group dynamics and trust towards\u0000a robot and pave the path to future research directions on moment-to-moment\u0000fairness perceptions","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SIS: Seam-Informed Strategy for T-shirt Unfolding SIS： T恤展开的接缝信息战略

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.06990

Xuzhao Huang, Akira Seino, Fuyuki Tokuda, Akinari Kobayashi, Dayuan Chen, Yasuhisa Hirata, Norman C. Tien, Kazuhiro Kosuge

引用次数: 0

Single-View 3D Reconstruction via SO(2)-Equivariant Gaussian Sculpting Networks 通过 SO(2)-Equivariant 高斯雕刻网络进行单视角三维重建

arXiv - CS - Robotics Pub Date : 2024-09-11 DOI: arxiv-2409.07245

Ruihan Xu, Anthony Opipari, Joshua Mah, Stanley Lewis, Haoran Zhang, Hanzhe Guo, Odest Chadwicke Jenkins

引用次数: 0