Research on autonomous path planning and tracking control methods for unmanned electric shovels

IF 8.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-21 DOI:10.1111/mice.13402

Xiaodan Tan, Guoqiang Wang, Guohua Wu, Zongwei Yao, Yongpeng Wang, Qingxue Huang

引用次数: 0

Abstract

Achieving fully unmanned operations in large‐scale excavating machinery relies on robust autonomous driving capabilities. Electric shovels, with their steering limitations and reversing difficulties, present unique challenges, compared to lighter, high‐speed‐tracked vehicles. This paper explores these operational and technical challenges and introduces a trajectory planning scheme combining the Guidance‐Hybrid A* algorithm with the dynamic window approach. A high‐precision tracking controller with adjustable factors was also developed. Simulation results show that this approach enhances path‐searching efficiency and prevents reversing paths, with heading error control within 5°. Prototype experiments confirmed the controller's superiority in computational response speed and control stability, maintaining high precision at 0.1 m.

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来源期刊

Computer-Aided Civil and Infrastructure Engineering 工程技术-工程：土木

CiteScore

17.60

自引率

19.80%

发文量

146

审稿时长

1 months

期刊介绍： Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.