Abstract
Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the conventional A* algorithm and the subsequent improved algorithms still have some limitations in terms of robustness and efficiency. These limitations include slow algorithm efficiency, weak robustness, and collisions when robots are traversing. In this paper, we propose an improved A*-based algorithm called EBHSA* algorithm. The EBHSA* algorithm introduces the expansion distance, bidirectional search, heuristic function optimization and smoothing into path planning. The expansion distance extends a certain distance from obstacles to improve path robustness by avoiding collisions. Bidirectional search is a strategy that searches for a path from the start node and from the goal node at the same time. Heuristic function optimization designs a new heuristic function to replace the traditional heuristic function. Smoothing improves path robustness by reducing the number of right-angle turns. Moreover, we carry out simulation tests with the EBHSA* algorithm, and the test results show that the EBHSA* algorithm has excellent performance in terms of robustness and efficiency. In addition, we transplant the EBHSA* algorithm to a robot to verify its effectiveness in the real world.
Highlights
Robots have been rapidly developed and widely used in the past decades, especially in typical transportation application scenarios such as airports, ports, warehousing, and logistics
The main contributions of this paper as follows: the EBHSA* algorithm is proposed in this paper, and it includes four optimization strategies in the traditional A* algorithm: expansion distance, bidirectional search, heuristic function optimization and smoothing
The experimental results show that the run-time of the EBHSA* algorithm was approximately 3.30% of that of the traditional A* algorithm, which means that the efficiency was 30.26 times that of the A* algorithm
Summary
Robots have been rapidly developed and widely used in the past decades, especially in typical transportation application scenarios such as airports, ports, warehousing, and logistics. The research problems are how to reduce the runtime of the algorithm and the number of search nodes, and how to avoid collision and reduce the number of right-angle turns To address these two issues, an improvement method named the EBHSA* algorithm is proposed in this paper. The main contributions of this paper as follows: the EBHSA* algorithm is proposed in this paper, and it includes four optimization strategies in the traditional A* algorithm: expansion distance, bidirectional search, heuristic function optimization and smoothing. In addition to test the effectiveness of the EBHSA* algorithm in actual application scenarios, the EBHSA* algorithm is transplanted to an FS-AIROBOTB mobile robot produced by China HuaQing YuanJian, and tested in the real world The rest of this manuscript is organized as follows.
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