Autonomous land vehicle path planning algorithm based on improved heuristic function of A-Star

Jing Zhang,Xiao Shen,Jun Wu,Yunsong Li

doi:10.1177/17298814211042730

Jing Zhang, Xiao Shen + Show 2 more

Open Access

https://doi.org/10.1177/17298814211042730

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Abstract

The path planning of autonomous land vehicle has become a research hotspot in recent years. In this article, we present a novel path planning algorithm for an autonomous land vehicle. According to the characteristics of autonomous movement towards the autonomous land vehicle, an improved A-Star path planning algorithm is designed. The disadvantages of using the A-Star algorithm for path planning are that the path planned by the A-Star algorithm contains many unnecessary turning points and is not smooth enough. Autonomous land vehicle needs to adjust its posture at each turning point, which will greatly waste time and also will not be conducive to the motion control of autonomous land vehicle. In view of these shortcomings, this article proposes a new heuristic function combined with the artificial potential field method, which contains both distance information and obstacle information. Our proposed algorithm shows excellent performance in improving the execution efficiency and reducing the number of turning points. The simulation results show that the proposed algorithm, compared with the traditional A-Star algorithm, makes the path smoother and makes the autonomous land vehicle easier to control.

Highlights

In recent years, autonomous land vehicle (ALV) has been widely used in emergency rescue, port freight, logistics distribution, and other fields
Aiming at the problem of unsmooth path of the A-Star algorithm, we propose a new heuristic function, which is combined with the artificial potential field to optimize the path and improve search efficiency
The calculation of the potential field force of the artificial potential field method is shown in Figure 3 In the artificial potential field, for a certain point in space, the ALV will be subjected to a force with a certain magnitude and direction

Summary

Introduction

Autonomous land vehicle (ALV) has been widely used in emergency rescue, port freight, logistics distribution, and other fields. The heuristic function of the A-Star algorithm only considered distance information, which leads to redundant expansion nodes in the pathfinding process. The above algorithms only consider the position of the obstacle in the global map but not consider the number of obstacles and distance around the ALV in the path planning process, which is not sufficient for the use of map information. Aiming at the problem of unsmooth path of the A-Star algorithm, we propose a new heuristic function, which is combined with the artificial potential field to optimize the path and improve search efficiency. Comparing the A-Star algorithm and proposed algorithm in the grid map environment, the result verifies that our method is more conducive to motion control and the planned path is smoother. In the grid map, the movement direction of the ALV is generally only 8, which are the directions of the 8 neighboring nodes of the grid map.[20]

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