高维构型空间线性图元的自适应连续碰撞检测

doi:10.13973/j.cnki.robot.2017.0769

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (626 KB) HTML ( ) 输出: BibTeX \| EndNote (RIS)
引用本文:
吴鸿敏, 张国英, 管贻生, 陈新. 高维构型空间线性图元的自适应连续碰撞检测[J]. 机器人, 2017, 39(6): 769-775.DOI: 10.13973/j.cnki.robot.2017.0769. WU Hongmin, ZHANG Guoying, GUAN Yisheng, CHEN Xin. Adaptive Continuous Collision Detection for Linear Segments in High Dimensional Configuration Space. ROBOT, 2017, 39(6): 769-775. DOI: 10.13973/j.cnki.robot.2017.0769.

摘要为了高效地建立无碰撞路径地图，针对如何在构型空间中构建无碰撞线性图元的问题，提出了自适应连续碰撞的检测算法.该算法在对线性图元进行连续碰撞检测之前，通过对比同一构型下两物体间欧氏距离的最小值及不同构型下物体最大移动距离的关系，来决定是否对线性图元采取二等分分割的细分检测，有效地减少了冗余的碰撞检测次数，提高地图构建效率.利用高维机器人系统进行仿真验证，在给定机器人起始和终止构型的情况下规划出无碰撞路径，所提的自适应碰撞检测算法相比于固定检测精度的方法的计算效率提高25.1%～84.1%.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	吴鸿敏
	张国英
	管贻生
	陈新

关键词 ：构型空间, 概率路径地图, 自适应碰撞检测, 运动规划, 多机器人系统

Abstract：In order to efficiently build the collision-free roadmap, an adaptive continuous collision detection algorithm is proposed to construct the collision-free linear segments in configuration space. Before performing continuous collision detection for the linear segments, the proposed method compares the minimal Euclidean distance of two static objects in a fixed configuration and the maximal displacement distance of specific objects in different configurations, to determine whether or not to bisect the linear segments for fine detection. So, the times of redundant detections are reduced effectively, and the mapping efficiency is improved. The proposed method is demonstrated by planning the collision-free path between the given starting and terminal configurations for a high dimensional robot simulation system. As a result, the computational efficiency of the proposed adaptive collision detection method is 25.1%~84.1% higher than the methods of fixed detection resolution.

Key words： configuration space probabilistic roadmap adaptive collision detection motion planning multiple robots system

收稿日期: 2017-02-14 录用日期: 2017-06-29

TP242

基金资助:国家自然科学基金（51375095）；国家基金委广东省联合基金重点项目（U1401240）；国际科技合作专项（2015DFA11700）；广东省自然科学基金重点项目（S2013020012797）；广东省前沿与关键技术创新专项资金（2014B090919002，2015B010917003，2016B090911002，2015B090922003）

通讯作者: 管贻生,ysguan@gdut.edu.cn E-mail: ysguan@gdut.edu.cn

作者简介: 吴鸿敏(1991-),男,博士生.研究领域:多机器人协调无碰运动规划,自主操作,人机共融
张国英(1980-),女,博士生,讲师.研究领域:机器人机构学,混联机器人综合性能设计
管贻生(1966-),男,博士,教授.研究领域:仿生机器人,模块化机器人,智能制造与自动化.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0769 或 https://robot.sia.cn/CN/Y2017/V39/I6/769

[1] LaValle S, Kuffner J. Randomized kinodynamic planning[J]. International Journal of Robotics Research, 2001, 20(5):378-400.
[2] Jaillet L, Cortes J, Simeon T. Sampling-based path planning on configuration-space costmaps[J]. IEEE Transactions on Robotics, 2010, 26(4):635-646.
[3] Xie B Y, Zhuo J, Liu Y. Motion planning of reaching point movements for 7R robotic manipulators in obstacle environment based on rapidly-exploring random tree algorithm[J]. Journal of Mechanical Engineering, 2012, 48(3):63-69.
[4] Latombe J C. Robot motion planning[M]//The Springer International Series in Engineering and Computer Science, vol.124. Berlin, Germany:Springer-Verlag, 2012.
[5] Saha M, Roughgarden T, Latombe J C, et al. Planning tours of robotic arms among partitioned goals[J]. International Journal of Robotics Research, 2006, 25(3):207-223.
[6] Isto P, Saha M. A slicing connection strategy for constructing PRMs in high-dimensional cspaces[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 2006:1249-1254.
[7] Kannan A, Gupta P, Tiwari R, et al. Robot motion planning using adaptive hybrid sampling in probabilistic roadmaps[J]. Electronics, 2016, 5(2):16-17.
[8] Schwarzer F, Saha M, Latombe J C. Exact collision checking of robot paths[J]. Springer Tracts in Advanced Robotics, 2004, 7(5):25-41.
[9] 潘佳,Dinesh M.运动规划的高效配置空间构建与优化[J].Engineering,2015,1(1):46-57.Pan J, Dinesh M. Efficient configuration space construction and optimization for motion planning[J]. Engineering, 2015, 1(1):46-57.
[10] Schwarzer F, Saha M, Latombe J C. Adaptive dynamic collision checking for single and multiple articulated robots in complex environments[J]. IEEE Transactions on Robotics, 2005, 21(3):338-353.
[11] Larsen E, Gottschalk S, Lin M C, et al. Fast distance queries with rectangular swept sphere volumes[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 2000:3719-3726.
[12] Wang H Y, Liu S G. A collision detection algorithm using AABB and octree space division[J]. Advanced Materials Research, 2014, 989(26):2389-2392.
[13] Canny J. Collision detection for moving polyhedral[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(2):200-209.
[14] Schweikard A. Polynomial time collision detection for manipulator paths specified by joint motions[J]. IEEE Transactions on Robotics and Automation, 1992, 7(6):865-870.
[15] Spensieri D, Carlson J S, Ekstedt F, et al. An iterative approach for collision free routing and scheduling in multirobot stations[J]. IEEE Transactions on Automation Science & Engineering, 2015, 13(2):1-13.
[16] 王伟,马峻,刘伟,等.基于OBB包围盒的碰撞检测研究与应用[J].计算机仿真,2009,26(9):180-183.Wang W, Ma J, Liu W, et al. Research and application of collision detection based oriented bounding box[J]. Computer Simulation, 2009, 26(9):180-183.
[17] Baginski B. Efficient dynamic collision detection using expanded geometry models[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA:IEEE, 1997:1714-1720.
[18] UNC GAMMA Group. Proximity query packages[EB/OL].[2016-11-13]. http://gamma.cs.unc.edu.
[19] Welzl E. Smallest enclosing disks (balls and ellipsoids)[M]//New Results and New Trends in Computer Science. Berlin, Germany:Springer-Verlag, 1991:359-370.