An improved A-Star based path planning algorithm for autonomous land vehicles

This article presents a novel path planning algorithm for autonomous land vehicles. There are four main contributions: Firstly, an evaluation standard is introduced to measure the performance of different algorithms and to select appropriate parameters for the proposed algorithm. Secondly, a guideli...

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Published in:	International journal of advanced robotic systems Vol. 17; no. 5
Main Authors:	Erke, Shang, Bin, Dai, Yiming, Nie, Qi, Zhu, Liang, Xiao, Dawei, Zhao
Format:	Journal Article
Language:	English
Published:	London, England SAGE Publications 01.09.2020 Sage Publications Ltd SAGE Publishing
Subjects:	Algorithms Computing time Obstacle avoidance Path planning Autonomous land vehicles improved A-Star key point path planning guideline
ISSN:	1729-8806, 1729-8814
Online Access:	Get full text
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Abstract	This article presents a novel path planning algorithm for autonomous land vehicles. There are four main contributions: Firstly, an evaluation standard is introduced to measure the performance of different algorithms and to select appropriate parameters for the proposed algorithm. Secondly, a guideline generated by human or global planning is employed to develop the heuristic function to overcome the shortcoming of traditional A-Star algorithms. Thirdly, for improving the obstacle avoidance performance, key points around the obstacle are employed, which would guide the planning path to avoid the obstacle much earlier than the traditional one. Fourth, a novel variable-step based A-Star algorithm is also introduced to reduce the computing time of the proposed algorithm. Compared with the state-of-the-art techniques, experimental results show that the performance of the proposed algorithm is robust and stable.
AbstractList	This article presents a novel path planning algorithm for autonomous land vehicles. There are four main contributions: Firstly, an evaluation standard is introduced to measure the performance of different algorithms and to select appropriate parameters for the proposed algorithm. Secondly, a guideline generated by human or global planning is employed to develop the heuristic function to overcome the shortcoming of traditional A-Star algorithms. Thirdly, for improving the obstacle avoidance performance, key points around the obstacle are employed, which would guide the planning path to avoid the obstacle much earlier than the traditional one. Fourth, a novel variable-step based A-Star algorithm is also introduced to reduce the computing time of the proposed algorithm. Compared with the state-of-the-art techniques, experimental results show that the performance of the proposed algorithm is robust and stable.
Author	Qi, Zhu Erke, Shang Dawei, Zhao Bin, Dai Yiming, Nie Liang, Xiao
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SubjectTerms	Algorithms Computing time Obstacle avoidance Path planning
Title	An improved A-Star based path planning algorithm for autonomous land vehicles
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