Port environmental path planning based on key obstacles

• Published in: Scientific reports Vol. 14; no. 1; pp. 21757 - 14
• Main Authors: Yang, Guoliang, Xiong, Wenkai
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18.09.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166; 639/166/988; Algorithms; Humanities and Social Sciences; multidisciplinary; Problem solving; Science; Science (multidisciplinary)
• DOI: 10.1038/s41598-024-72530-9
• ISSN: 2045-2322

This paper proposes an improved hybrid algorithm for automated guided vehicles (AGVs) in port environments based on the concept of key obstacles for the JPS and DWA algorithms. Given the complexity of the port environment and the abundance of obstacles, the traditional heuristic function of the JPS algorithm is improved by adding the key obstacle heuristic function. Simultaneously, improvements are made to the evaluation function of the traditional DWA algorithm, where the braking distance is segmented into key obstacle distance and non-key obstacle distance, utilizing the concept of key obstacles. Simulation experiments are conducted using Matlab to demonstrate the effectiveness of the improved algorithm. Moreover, the performance of the hybrid algorithm is compared with five mainstream algorithms in a real simulated port environment, and the final results show the significant enhancement of this paper’s algorithm in several key performance metrics. Thus, this study provides a feasible strategy for improved path planning efficiency for AGV in the port environment.