Improved Artificial Potential Field and Dynamic Window Method for Amphibious Robot Fish Path Planning

Wenlin Yang,Gong Zhang,Weijun Wang,Xiaokai Liu,Peng Wu,Xiaoqi Zhou,Haoliang Lv,Zhicheng Hou

doi:10.3390/app11052114

Abstract

Aiming at the problems of “local minimum” and “unreachable target” existing in the traditional artificial potential field method in path planning, an improved artificial potential field method was proposed after analyzing the fundamental causes of the above problems. The method solved the problem of local minimum by modifying the direction and influence range of the gravitational field, increasing the virtual target and evaluation function, and the problem of unreachable targets is solved by increasing gravity. In view of the change of motion state of robot fish in amphibious environments, the improved artificial potential field method was fused with a dynamic window algorithm, and a dynamic window evaluation function of the optimal path was designed on the basis of establishing the dynamic equations of land and underwater. Then, the simulation experiment was designed under the environment of Matlab2019a. Firstly, the improved and traditional artificial potential field methods were compared. The results showed that the improved artificial potential field method could solve the above two problems well, shorten the operation time and path length, and have high efficiency. Secondly, the influence of different motion modes on path planning is verified, and the result also reflects that the amphibious robot can avoid obstacles flexibly and reach the target point accurately according to its own motion ability. This paper provides a new way of path planning for the amphibious robot.

Highlights

Over the last few decades, mobile robots have been widely used in many circumstances, which improves the working efficiency and reduces the cost of work to a great extent, and these advantages show their great developmental potential [1,2,3]
Many scholars have studied the improved algorithm to further improve its performance. It is usually used as follows: through the improvement of the gravitational field model to avoid the problem of encountering obstacles, when the distance is too far and the gravitational force is too large; on the basis of the original repulsion field and considering the influence of the relative position and velocity between the target and the robot, a new repulsion function is introduced to reduce the strength of the repulsion potential field of the obstacle near the target, and solve the problem that the obstacle near the target leads to an unreachable target
In this paper, an improved path planning algorithm for an amphibious robot is proposed, which overcomes the shortcomings of the existing algorithm

Summary

Introduction

Over the last few decades, mobile robots have been widely used in many circumstances, which improves the working efficiency and reduces the cost of work to a great extent, and these advantages show their great developmental potential [1,2,3]. Amphibious robotic fish in mobile robots are the object of this study This is an underwater robot with the efficient propulsion function of fish, and an overland robot adapted to complex terrestrial environments. In order to achieve this goal, many scholars have done a lot of research and put forward many feasible algorithms. These algorithms can be divided into global path planning algorithms [7,8] and local path planning algorithms [9]. Each algorithm has its corresponding advantages and disadvantages in different scenarios, so it is necessary to apply the most appropriate algorithm in light of the actual conditions

Objectives

Discussion

Conclusion