Efficient Template-based Path Imitation by Invariant Feature Mapping

摘要：

We propose a novel approach for robot movement imitation that is suitable for robotic arm movement in tasks such as reaching and grasping. This algorithm selects a previously observed path demonstrated by an agent and generates a path in a novel situation based on pairwise mapping of invariant feature locations present in both the demonstrated and the new scenes using minimum distortion and minimum energy strategies. This One-Shot Learning algorithm is capable of not only mapping simple pointto- point paths but also adapting to more complex tasks such as involvement of forced waypoints. As compared to traditional methodologies, our work does not require extensive training for generalisation as well as expensive run-time computation for accuracy. Cross-validation statistics of grasping experiments show great similarity between the paths produced by human subjects and the proposed algorithm.

关键词： movement imitation path planning grasping learning by imitation

作者: Yan Wu Yiannis Demiris

作者单位: Department of Electrical & Electronic Engineering,Imperial College London,United Kingdom

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 913-918

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）