2010 IEEE/RSJ International Conference on Intelligent Robots and Systems最新文献_第8页

Learning-based control strategy for safe human-robot interaction exploiting task and robot redundancies 利用任务和机器人冗余的基于学习的安全人机交互控制策略

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5648931

S. Calinon, I. Sardellitti, D. Caldwell

引用次数: 162

Fault-tolerant probabilistic sensor fusion for Multi-Agent Systems 多智能体系统的容错概率传感器融合

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5650337

Abdolkarim Pahliani, M. Spaan, P. Lima

引用次数: 3

Distributed control architecture for smart surfaces 智能表面的分布式控制体系结构

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5650668

Kahina Boutoustous, G. Laurent, Eugen Dedu, L. Matignon, J. Bourgeois, N. L. Fort-Piat

引用次数: 46

The D++ algorithm: Real-Time and collision-free path-planning for mobile robot D++算法:移动机器人实时无碰撞路径规划

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5652124

P. Cheng, Pin-Jyun Chen

引用次数: 4

Real-time moving object recognition and tracking using computation offloading 基于计算卸载的实时运动目标识别与跟踪

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5650303

Yamini Nimmagadda, Karthik Kumar, Yung-Hsiang Lu, C. S. G. Lee

引用次数: 87

Optimal design and fabrication of a piezoactuated flexure XYZ parallel micropositioning stage 压电驱动柔性XYZ并联微定位台的优化设计与制造

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5652166

Qingsong Xu, Yangmin Li

引用次数: 12

IQ-ASyMTRe: Synthesizing coalition formation and execution for tightly-coupled multirobot tasks IQ-ASyMTRe:紧密耦合多机器人任务的综合联盟形成与执行

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5651186

Yu Zhang, L. Parker

{"title":"IQ-ASyMTRe: Synthesizing coalition formation and execution for tightly-coupled multirobot tasks","authors":"Yu Zhang, L. Parker","doi":"10.1109/IROS.2010.5651186","DOIUrl":"https://doi.org/10.1109/IROS.2010.5651186","url":null,"abstract":"This paper presents the IQ-ASyMTRe architecture, which is aimed to address both coalition formation and execution for tightly-coupled multirobot tasks in a single framework. Many task allocation algorithms have been previously proposed without explicitly enabling the sharing of robot capabilities. Inspired by information invariant theory, ASyMTRe was introduced which enables the sharing of sensory and computational capabilities by allowing information to flow among different robots via communication. However, ASyMTRe does not provide a solution for how a coalition should satisfy sensor constraints introduced by the sharing of capabilities while executing the assigned task. Furthermore, conversions among different information types1 are hardcoded, which limits the flexibility of ASyMTRe. Moreover, relationships between entities (e.g., robots) and information types are not explicitly captured, which may produce infeasible solutions from the start, as the defined information type may not correspond well to the current environment settings. The new architecture introduces a complete definition of information type to guarantee the feasibility of solutions; it also explicitly models information conversions. Inspired by our previous work, IQ-ASyMTRe uses measures of information quality to guide robot coalitions to satisfy sensor constraints (introduced by capability sharing) while executing tasks, thus providing a complete and general solution. We demonstrate the capability of the approach both in simulation and on physical robots to form and execute coalitions that share sensory information to achieve tightly-coupled tasks.","PeriodicalId":420658,"journal":{"name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":"64 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879437","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: 26

Time-delayed bilateral teleoperation with force estimation for n-DOF nonlinear robot manipulators 基于力估计的n-DOF非线性机器人时滞双边遥操作

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5649183

J. Daly, David W. L. Wang

引用次数: 27

Robust online map merging system using laser scan matching and omnidirectional vision 基于激光扫描匹配和全向视觉的鲁棒在线地图合并系统

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5654446

Fredy Tungadi, W. Lui, L. Kleeman, R. Jarvis

{"title":"Robust online map merging system using laser scan matching and omnidirectional vision","authors":"Fredy Tungadi, W. Lui, L. Kleeman, R. Jarvis","doi":"10.1109/IROS.2010.5654446","DOIUrl":"https://doi.org/10.1109/IROS.2010.5654446","url":null,"abstract":"This paper describes a probabilistic online map merging system for a single mobile robot. It performs intermittent exploration by fusing laser scan matching and omnidirectional vision. Moreover, it can also be adapted to a multi-robot system for large scale environments. Map merging is achieved by means of a probabilistic Haar-based place recognition system using omnidirectional images and is capable of discriminating new and previously visited locations in the current or previously collected maps. This dramatically reduces the search space for laser scan matching. The combination of laser range finding and omnidirectional vision is very attractive because they reinforce one another when there is sufficient structure and visual information in the environment. In other cases, they complement one another, leading to improved robustness of the system. This is the first system to combine a probabilistic Haar-based place recognition system using omnidirectional images with laser range finding to merge maps. The proposed system is also algorithmically simple, efficient and does not require any offline processing. Experimental results of the approach clearly illustrate that the proposed system can perform both online map merging and exploration robustly using a single robot configuration in a real indoor lab environment.","PeriodicalId":420658,"journal":{"name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115443715","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: 27

Temporal scaling of leg motion for music feedback system of a dancing humanoid robot 人形舞蹈机器人音乐反馈系统腿部运动的时间尺度

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI: 10.1109/IROS.2010.5652811

Takahiro Okamoto, Takaaki Shiratori, S. Kudoh, K. Ikeuchi

引用次数: 7