Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot

• Published in: Journal of intelligent & robotic systems Vol. 102; no. 4; p. 78
• Main Authors: Lai, Xin, Li, JiaHe, Chambers, Jonathon
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2021; Springer; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Control; Electrical Engineering; Engineering; Heuristic; Inspection; Mechanical Engineering; Mechatronics; Nodes; Path planning; Petroleum chemicals industry; Response time; Robotics; Robots; Search process; Short Paper; Shortest path planning; Heuristic function; Path planning; CCWA algorithm; Dynamic weights
• ISSN: 0921-0296; 1573-0409
• DOI: 10.1007/s10846-021-01437-8

In many practical applications of robot path planning, finding the shortest path is critical, while the response time is often overlooked but important. To address the problems of search node divergence and long calculation time in the A* routing algorithm in the large scenario, this paper presents a novel center constraint weighted A* algorithm (CCWA*). The heuristic function is modified to give different dynamic weights to nodes in different positions, and the node weights are changed in the specified direction during the expansion process, thereby reducing the number of search nodes. An adaptive threshold is further added to the heuristic function to enhance the adaptiveness of the algorithm. To verify the effectiveness of the CCWA* algorithm, simulations are performed on 2-dimensional grid maps of different sizes. The results show that the proposed algorithm speeds up the search process and reduces the planning time in the process of path planning in a multi-obstacle environment compared with the conventional A* algorithm and weighted A* algorithm.