A DMPs-based Switching Motion Planning Method for Robots with Obstacles
- Resource Type
- Conference
- Authors
- Wu, Haocun; Zhai, Di-Hua; Xia, Zhiqiang; Xia, Yuanqing
- Source
- 2020 39th Chinese Control Conference (CCC) Chinese Control Conference (CCC), 2020 39th. :3875-3880 Jul, 2020
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Trajectory
Collision avoidance
Robots
Dynamics
Shape
Planning
Heuristic algorithms
Dynamic Movement Primitives
obstacle avoidance
robot
potential field
switching strategy
- Language
- ISSN
- 1934-1768
Recent studies of obstacle avoidance under the Dynamic Movement Primitives (DMPs) framework are limited on the dotted obstacles. A novel obstacle avoidance algorithm based on DMPs is proposed for shaped obstacle avoidance. By combining the steering behavior method and the potential field method with the evaluation of Euclidean distance, while absorbing the switching strategy, this new algorithm performs well in mimicking the learned DMPs trajectory and handles the fluctuations occur in the initial stage of motion. The simulations of 2D DMPs trajectory learning of one-obstacle avoidance and multi-obstacle avoidance show that the algorithm is feasible with figurate obstacles, and acquires great conformability with the learned trajectory and smoothness.