一种可变形机器人路径规划方法研究
文献类型：会议论文
| 作者 | 刘同林; 吴成东; 李斌 ; 刘金国
|
| 出版日期 | 2010 |
| 会议名称 | 2010 8th World Congress on Intelligent Control and Automation (WCICA 2010) |
| 会议日期 | July 7-9, 2010 |
| 会议地点 | Jinan, China |
| 关键词 | 可重构 模块 机器人 可变形 路径规划 |
| 页码 | 96-101 |
| 其他题名 | A Path Planning Method for a Shape-shifting Robot |
| 通讯作者 | 刘同林 |
| 中文摘要 | 可变形机器人AMOEBA-I 具有多种构形方式，通过构形的改变可以增强机器人在狭窄空间中的通过能力。针对机器人特有的变形能力，本文提出了种路径规划方法。这种方法能够根据机器人周围环境中障碍的分布情况自动调整计算量，并能够根据狭窄通道的宽度自动选择构形，使机器人能够快速安全地到达目标，以充分发挥可变形机器人特有的通过性能。采用边界跟踪的方法，有效地解决了死锁情况。通过仿真实验证明机器人能够根据环境变化改变自身构形完成路径规划，有效地缩短路径的长度，验证了算法的有效性。 |
| 英文摘要 | A shape-shifting robot, which named "AMOEBA-I", has diverse configurations. The accessibility of the robot can be reinforced in the narrow space by changing the configurations. In this paper, a path planning method is presented corresponding to the unique reconfigurable ability of the robot. This method can automatically adjust the computational cost according to the distribution of obstacles in robot's surrounding environment and can automatically select the configuration according to the width of the narrow space. So the robot can reach the target quickly and safely, and the unique accessibility of the shape-shifting robot is fully displayed. The deadlock situation is effectively solved by using the method of the boundary following. It has been validated through simulation results that the robot can change its own configurations to perform the path planning according to the environmental variation. As a result, the length of the path has been reduced effectively. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议主办者 | IEEE |
| 会议录 | 2010 8th World Congress on Intelligent Control and Automation (WCICA 2010)
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 中文 |
| ISBN号 | 978-1-4244-6712-9 |
| WOS记录号 | WOS:000295959500020 |
| 源URL | [http://ir.sia.cn/handle/173321/8961]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | 刘同林,吴成东,李斌,等. 一种可变形机器人路径规划方法研究[C]. 见:2010 8th World Congress on Intelligent Control and Automation (WCICA 2010). Jinan, China. July 7-9, 2010. |
入库方式： OAI收割
来源：沈阳自动化研究所
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