A Path Planning Method for Indoor Robots Based on Partial & Global A-Star Algorithm
Kang-le Wang, Shu-wen Dang, Fa-jiang He, Peng-zhan Cheng
Available Online April 2017.
- https://doi.org/10.2991/fmsmt-17.2017.83How to use a DOI?
- A-Star Algorithm; Indoor Robot; Path Planning; LIDAR
- Considering the traditional A*algorithm being difficult to satisfy the limitation of the indoor environment space of the robot. A partial and global A-Star (P&G-A*) algorithm based on the motion model of indoor robot is proposed. LIDAR sensing system is employed into P&G-A* algorithm to achieve both local awareness and global optimization. The real environment data is adopted for simulated experiments, and experimental results proved that the path planning time is reduced 13.31% when comparing with traditional algorithm, and actual driving distance decrease by 15.71%. Furthermore, the robot trajectory is more smoothly after P&G-A* is applied
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Kang-le Wang AU - Shu-wen Dang AU - Fa-jiang He AU - Peng-zhan Cheng PY - 2017/04 DA - 2017/04 TI - A Path Planning Method for Indoor Robots Based on Partial & Global A-Star Algorithm BT - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017) PB - Atlantis Press SP - 395 EP - 398 SN - 2352-5401 UR - https://doi.org/10.2991/fmsmt-17.2017.83 DO - https://doi.org/10.2991/fmsmt-17.2017.83 ID - Wang2017/04 ER -