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Path planning with the derivative of heuristic angle based on the GBFS algorithm.
1R&D 2 Team, Vessel Aerospace Co., Ltd., Suwon-si, South Korea.
Frontiers in Robotics and AI
|September 5, 2022
Summary
This study introduces WA*DH+, an improved robot path planning algorithm. It finds optimal paths faster in extreme environments by enhancing initial solutions, outperforming the original WA*DH.
Area of Science:
- Robotics
- Artificial Intelligence
- Path Planning Algorithms
Background:
- Robots operating in extreme environments require high reactivity.
- Fast response necessitates efficient path planning to find optimal routes quickly.
Purpose of the Study:
- Introduce WA*DH+, an enhanced version of the weighted A* with the derivative of heuristic angle (WA*DH) algorithm.
- Address limitations of WA*DH in finding suboptimal nodes with small inflation factors.
Main Methods:
- Developed WA*DH+ by inflating the suboptimality of the initial solution.
- Utilized the Greedy Best-First Search (GBFS) algorithm with an infinitely bounded suboptimal solution for the initial path.
Main Results:
- WA*DH+ successfully finds suboptimal nodes that WA*DH struggles with.
- Simulations show WA*DH+ returns better solutions more rapidly than WA*DH.
Conclusions:
- WA*DH+ offers improved performance for robot path planning in challenging environments.
- The enhanced approach enables faster identification of optimal paths for reactive robots.
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