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Subplanner Algorithm to Escape from Local Minima for Artificial Potential Function Based Robotic Path Planning
Int. J. Fuzzy Log. Intell. Syst. 2018;18(4):263-275
Published online December 25, 2018
© 2018 Korean Institute of Intelligent Systems.

Han Ul Yoon1 and Dong-Wook Lee1,2

1Robotics R&D Group, Korea Institute of Industrial Technology, Ansan, Korea 2Department of Robotics and Virtual Engineering, Korea University of Science and Technology, Daejon, Korea
Correspondence to: Dong-Wook Lee (dwlee@kitech.re.kr)
Received August 11, 2018; Revised November 1, 2018; Accepted November 13, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper proposes a subplanner algorithm, which will be referred to as attractive force rotation and restoration, to compensate the local minima problem under the artificial potential based planner. The key role of the proposed subplanner is to build a navigating path for escaping from the local minima by rotating and restoring the attractive force. A mobile manipulator was adopted as our robotic application to substantiate the capability of the proposed subplanner under various simulation scenarios in which the mobile manipulator finds a path to a target object without collision against stationary/moving obstacles. The simulation results substantiated that the compensated artificial potential based planner successfully found a path to guide the mobile manipulator to the target object in the presence of the local minima.
Keywords : Path planning, Mobile manipulator, Artificial potential based planner, Attractive force rotation and restoration algorithm