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A review on path planning and intelligent navigation of deep-sea mining vehicleOA

中文摘要

Deep-sea polymetallic nodules are characterized by their high grade and enormous reserves,and their commercial development is of great significance in addressing the shortage of terrestrial resources.Locomotion technology of mining vehicles is a core component of mining systems,and it directly determines the efficiency and productivity of collection operations.The feasibility verification stage remains in most existing research and technologies,and a large-scale,intelligent,and highly reliable locomotion technology system has not yet been established.Based on the basic dynamic characteristics of mining vehicles,this review systematically consolidates the research on structural optimization of vehicles,motion control,and dynamic coupling with trajectory control systems,and provides an integrated perspective connecting these domains with recent advances in path planning and intelligent navigation for deep-sea polymetallic nodule collection.It further examines path planning and navigation control in extreme environments by analyzing the inherent mechanisms of traction failure,along with existing prediction models and classical algorithms.The study identified theoretical gaps in the multibody dynamics analysis of deep-sea mining vehicles,outlined emerging trends in trajectory control,and clarified the challenges related to reliability and intelligence under extreme operating conditions.This integrative approach highlights the systemic interactions overlooked in previous studies,and proposes a novel framework for the development of intelligent mining vehicle in the future.In addition,some key future research directions aimed at laying a solid foundation for the commercial development of deep-sea polymetallic nodules were identified.

Fei Sha;Zeqian Li;Xuguang Chen;Yuhang Zuo

College of Engineering,Ocean University of China,Qingdao 266404,ChinaCollege of Engineering,Ocean University of China,Qingdao 266404,ChinaCollege of Engineering,Ocean University of China,Qingdao 266404,ChinaCollege of Engineering,Ocean University of China,Qingdao 266404,China

矿业与冶金

Deep-sea miningCrawler vehicleDynamic characteristicsPath planningIntelligent navigation

《Green and Smart Mining Engineering》 2026 (1)

P.1-15,15

supported by the National Science Fund for Distinguished Young Scholars(No.52225107)Fundamental Research Funds for the Central Universities(No.202442004)National Natural Science Foundation of China(Nos.U25A6020 and 51909140)Shandong Provincial University Youth Innovation Science and Technology Support Program(No.2021KJ034).

10.1016/j.gsme.2025.12.002

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