Path planning for unmanned surface vehicle based on predictive artificial potential field

Jia Song,Jiangcheng Su,Ce Hao

doi:10.1177/1729881420918461

Abstract

The path planning for high-speed unmanned surface vehicle raises more complicated requirements to reduce sailing time and save energy. In this article, a new predictive artificial potential field is proposed using time information and predictive potential to plan a smoother path. The principle of artificial potential field with vehicle dynamics and reachability in local minimum is studied. According to global and local path planning, the most state-of-the-art traditional artificial potential field and its drawback are analysed at first. Then we proposed predictive artificial potential field with three modifications: angle limit, velocity adjustment and predictive potential to improve the feasibility and flatness of the generated path. In addition, we compare the performance between traditional artificial potential field and predictive artificial potential field, where predictive artificial potential field successfully restricts the maximum turning angle, cuts short sailing time and intelligently avoids obstacle. From the simulation results, we also verify that predictive artificial potential field can solve concave local minimum problem and enhance the reachability in special scenario. Therefore, the more reasonable path generated by predictive artificial potential field reduces sailing time and helps conserve more energy for unmanned surface vehicle.

Highlights

During the past decades, a growing number of unmanned surface vehicles (USVs) have been developed for economic, environmental and robotic research applications.[1,2] We, human, start to rely more on USVs to explore complicated and changeable maritime space
The wide applications of USV driving a rising demand vary from the scenario in North America, and the European market is showing important development.[7]
We propose predictive artificial potential field (PAPF) method for USV path planning according to dynamic constraints and predictive ability

Summary

Introduction

A growing number of unmanned surface vehicles (USVs) have been developed for economic, environmental and robotic research applications.[1,2] We, human, start to rely more on USVs to explore complicated and changeable maritime space. Because many laborious tasks like commercial shipping,[3] hydrographic survey[4] and ocean rescue[5] are more suitable for unmanned vehicle, especially for economic purpose, the USVs can replace human to execute repetitive tasks, which definitely save much cost and energy.[6]. The importance of unmanned vehicles in the ocean exploration has been addressed by a large number of countries.

Methods

Findings

Discussion

Conclusion