Research on Path Planning by a Tangent Point Search
Ge Tai, Chaoyi Dong, Kang Zhang, Shuai Xiang, Tianyu Yuan, Haoda Yan, Xiaoyan Chen · 2024
When traditional path planning algorithms are used for path searching for Automated Guided Vehicles (AGVs) in static environments, they usually encounter the difficulties of excessive search nodes, high memory consumption, and long running time. To tackle these problems, this paper proposes a tangent point search algorithm based on quadtree grid environment modeling. The algorithm establishes a weighted graph by extracting key cell points and then uses the Dijkstra algorithm for path planning. In the scenarios of different map sizes, A* algorithm, Rapidly-exploring Random Trees (RRT) algorithm, Dijkstra algorithm, and a Dijkstra algorithm with a tangent point search (DA+TPS) were simulated and analyzed. The results show that among the four algorithms, the DA+TPS has the shortest route length and minimum search time. The comparison demonstrates that the proposed method can effectively reduce the number of search nodes, speed up the search process, and reduce redundant nodes in the path, thus reducing the number of turns for AGVs.