基于双向RRT算法的仿人机器人抓取操作

doi:10.3969/j.issn.0253-2778.2016.01.003

中国科学技术大学学报 ›› 2016, Vol. 46 ›› Issue (1): 12-20.DOI: 10.3969/j.issn.0253-2778.2016.01.003

• 论著 • 上一篇

基于双向RRT算法的仿人机器人抓取操作

杜爽，尚伟伟，刘坤，王智灵

1.中国科学技术大学，中国科学院空间信息处理与应用系统技术重点实验室，安徽合肥 230027； 2.中国科学院合肥物质科学研究院，安徽合肥 230031

收稿日期:2015-05-19 修回日期:2015-11-05 接受日期:2015-11-05 出版日期:2015-11-05 发布日期:2015-11-05
通讯作者: 尚伟伟
作者简介:杜爽，女，1990年生，硕士生，研究方向：仿人机器人运动规划.E-mail: dushuang@mail.ustc.edu.cn
基金资助:
国家自然科学基金(51275500)，机械系统与振动国家重点实验室开放基金（MSV201502）资助.

Bidirectional RRT algorithm based grasping manipulation of humanoid robots

DU Shuang, SHANG Weiwei, LIU Kun, WANG Zhiling

1. CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei 230027, China; 2. Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

Received:2015-05-19 Revised:2015-11-05 Accepted:2015-11-05 Online:2015-11-05 Published:2015-11-05

摘要/Abstract

摘要： 为了实现实际应用中的有效抓取操作，需要对仿人机器人进行全身运动规划.在全身运动规划中，必须考虑所有关节的自由度以及机器人、环境和被抓取对象物理特性的约束.针对这种包含多自由度、复杂约束的运动规划问题，设计了一种基于双向RRT算法的规划方法，获取了机器人的双腿稳定位形和抓取手的位姿序列，从而实现了仿人机器人的全身运动规划.最后，在仿人机器人NAO平台上进行了实验验证，完成了开抽屉、有障碍物情况下的开抽屉以及开抽屉取物并关闭抽屉等任务.实验结果表明，所设计的基于双向RRT算法的全身运动规划方法能够有效地解决仿人机器人的抓取操作问题.

关键词: 仿人机器人, 全身运动规划, 抓取, 快速搜索随机树（RRTs）, NAO

Abstract: To realize grasping manipulation effectively in practical application, whole-body motion planning should be designed for humanoid robots. Thus, degrees of freedom of all the joints in humanoid robots, and constraints of robots, environment and the physical characteristics of grasped objects should be taken into consideration. To solve the problems including multi degrees of freedom and complex constraints, a new planning method is designed by using bidirectional RRT algorithm. After receiving stable double-leg configurations and the list of grasping hand’s poses, the bidirectional RRT algorithm is adopted to realize the whole-body motion planning for humanoid robots. Some experiments are conducted to make a NAO humanoid robot to open a drawer, enables to open a drawer in the presence of obstacles, and open a drawer for taking an object, and close the drawer. The results indicate that the whole-body motion planning with bidirectional RRT algorithm is effective in achieving the grasping manipulation of humanoid robots.

Key words: humanoid robot, whole-body motion planning, grasp, rapidly-exploring random trees (RRTs), NAO

中图分类号:

TP242

杜爽，尚伟伟，刘坤，王智灵. 基于双向RRT算法的仿人机器人抓取操作[J]. 中国科学技术大学学报, 2016, 46(1): 12-20.

DU Shuang, SHANG Weiwei, LIU Kun, WANG Zhiling. Bidirectional RRT algorithm based grasping manipulation of humanoid robots[J]. Journal of University of Science and Technology of China, 2016, 46(1): 12-20.

参考文献

［1］
Tsuji T, Harada K, Kaneko K, et al. Selecting a suitable grasp motion for humanoid robots with a multi-fingered hand［C］// IEEE-RAS International Conference on Humanoid Robots. Daejeon, Korea: IEEE Press, 2008: 54-60.
［2］ Dalibard S, Nakhaei A, Lamiraux F, et al. Whole-body task planning for a humanoid robot: A way to integrate collision avoidance［C］// IEEE-RAS International Conference on Humanoid Robots. Paris, France: IEEE Press, 2009: 355-360.
［3］ Stilman M. Global manipulation planning in robot joint space with task constraints［J］. IEEE Transactions on Robotics and Automation, 2010, 26(3): 576-584.
［4］ Kavraki L E, Svestka P, Latombe J C, et al. Probabilistic roadmaps for path planning in high-dimensional configuration spaces［J］. IEEE Transactions on Robotics and Automation, 1996, 12(4): 566-580.
［5］ LaValle S M. Rapidly-exploring random trees: A new tool for path planning［R］. Department of Computer Science, Iowa State University, Ames, Technique Report 98-11, 1998.
［6］ LaValle S M, Kuffner J. Rapidly-exploring random trees: Progress and prospects［C］// Proceedings of Workshop on Algorithmic Foundations of Robotics. 2000: 293-308.
［7］ Kuffner J J, Lavalle S M. RRT-Connect: An efficient approach to single-query path planning［C］// Proceedings of the IEEE International Conference on Robotics & Automation. San Francisco, USA: IEEE Press, 2000, 2: 995-1001.
［8］ Kuffner J, Nishiwaki K, Kagami S, et al. Motion planning for humanoid robots under obstacle and dynamic balance constraints［C］// Proceedings of the IEEE International Conference on Robotics & Automation. Albuquerque, New Mexico: IEEE Press, 2001: 692-698.
［9］ Burget F, Hornung A, Bennewitz M. Whole-body motion planning for manipulation of articulated objects［C］// Proceedings of the IEEE International Conference on Robotics & Automation. Karsruhe, Germany: IEEE Press, 2013: 1656-1662.
［10］ LaValle S M. Planning Algorithms［M］. Cambridge, UK: Cambridge University Press, 2006.
［11］王维,李焱. 基于RRT的虚拟人双臂操控规划方法［J］. 系统仿真学报, 2009, 21(20): 6515-6518.
Wang Wei, Li Yan. RRT-based manipulation planning method for both arms of virtual human［J］. Journal of System Simulation, 2009, 21(20): 6515-6518.

()
()

基于双向RRT算法的仿人机器人抓取操作

Bidirectional RRT algorithm based grasping manipulation of humanoid robots

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics

本文评价