A novel motion planning method is proposed to generate human-like motion for anthropomorphic robot arms. Its highlight is to consider the robot arm to be human-like not only in its configuration but also in its motion patterns. To achieve this, the intrinsic mechanisms of human arm motion generation are transferred to robot motion planning. First, human arm motion is modeled using human arm motion primitives. The mechanisms of human arm motion generation are dissected from a large number of motion samples, reflected in the types, sequencing and quantification rules/laws of the primitives. Next, the human arm motion patterns are studied based on primitive chains. Finally, a new motion planning method is built that autonomously performs motion pattern decisions, motion time allocation, and joint trajectory generation. The proposed method is validated by a motion planning app and a robot simulation.
|Title of host publication||2021 IEEE International Conference on Robotics and Automation, ICRA 2021|
|Number of pages||7|
|State||Published - 2021|
|Event||2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China|
Duration: May 30 2021 → Jun 5 2021
|Name||Proceedings - IEEE International Conference on Robotics and Automation|
|Conference||2021 IEEE International Conference on Robotics and Automation, ICRA 2021|
|Period||5/30/21 → 6/5/21|
Bibliographical noteFunding Information:
* Research supported by the National Natural Science Foundation of China (No. 51975008) and Beijing Municipal Natural Science Foundation (No. 3192002) Shiqiu Gong and Jing Zhao are with the College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, China. (E-mail: gsq01041@ emails.bjut.edu.cn).
© 2021 IEEE
ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering