Skill robot library: Intelligent path planning framework for object manipulation
Skill robot library: Intelligent path planning framework for object manipulation
复制标题
技能机器人库：物体操纵的智能路径规划框架
DOI：
10.23919/eusipco.2017.8081640
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
A. Gräser
中科院分区：
文献类型：
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作者：
Maria Kyrarini;Sameer Naeem;Xingchen Wang;A. Gräser
常用的路径规划技术的对象操作是计算昂贵和耗时的。提出了一种新的机器人技能库（Skill Robot Library，SRL）框架，该框架只存储路径的关键点，而不存储完整的路径。路径可以用路径规划器计算或由人使用动觉教学来教授。另外，当环境是静态的并且仅所请求的新的开始位置和目标位置相对于所存储的路径的开始位置和目标位置改变时，SRL可以检索并修改所存储的路径ARL将最终路径转发给机器人以用于再现。与六个自由度的机器人手臂的实验结果一起提出的SRL和路径规划器的性能评价，通过一系列的实验证明。
Commonly used path planning techniques for object manipulation are computationally expensive and time-consuming. In this paper, a novel framework called Skill Robot Library (SRL), which has competence to store only the keypoints of a path rather than complete, is presented. The path can be computed with path planner or taught by a human using kinesthetic teaching. Additionally, when the environment is static and only the requested new start and goal positions are changed with respect to the start and goal positions of the stored path, the SRL can retrieve and modify the stored path. The SRL forwards the final path to the robot for reproduction. Experimental results achieved with a six degrees of freedom robotic arm are presented together with performance evaluation of the SRL and the path planner is demonstrated via a series of experiments.