Volume 6, Issue 4, March 2020, Pages 240 - 245
Real-time Planning Robotic Palletizing Tasks using Reusable Roadmaps
Takumi Sakamoto1, *, Kensuke Harada1, 2, Weiwei Wan1, 3
1Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka 560-8531, Japan
2Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-3-36, Aomi, Koto-ku, Tokyo 135-0064, Japan
3Intelligent Systems Research Institute, Advanced Industrial Science and Technology (AIST), 1-1 Umezono, Tsukuba 305-8560, Japan
*Corresponding author. Email: email@example.com
Received 7 December 2019, Accepted 18 December 2019, Available Online 29 February 2020.
- 10.2991/jrnal.k.200222.009How to use a DOI?
- Palletizing; de-palletizing; motion planning; path planning; PRM; RRT*
This paper focuses on robotic motion planning for performing the palletizing or de-palletizing tasks. In such tasks, a robot usually iterates similar pick-and-place for several times. Considering such feature of the tasks, we propose two motion planning approaches named reusable Probabilistic Roadmap Method (PRM) and reusable Rapidly-exploring Random Tree Star (RRT*) where both methods utilize the previously constructed roadmaps in the conventional PRM and RRT*, respectively. We experimentally confirm that both methods significantly save the calculation time needed for motion planning compared to the conventional planning methods.
- © 2020 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
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TY - JOUR AU - Takumi Sakamoto AU - Kensuke Harada AU - Weiwei Wan PY - 2020 DA - 2020/02/29 TI - Real-time Planning Robotic Palletizing Tasks using Reusable Roadmaps JO - Journal of Robotics, Networking and Artificial Life SP - 240 EP - 245 VL - 6 IS - 4 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.k.200222.009 DO - 10.2991/jrnal.k.200222.009 ID - Sakamoto2020 ER -