A route replanning method and system for an unmanned mine car

By improving the Hybrid A* path planning and trajectory optimization algorithm, and combining multi-dimensional dynamic factors to evaluate the battery swapping route of the unmanned mining truck, the problem of unreasonable battery swapping path planning in the existing technology is solved, realizing a more efficient and orderly battery swapping process, and improving the operational continuity and system coordination of the unmanned mining truck.

CN122151934APending Publication Date: 2026-06-05SHANGHAI BOONRAY INTELLIGENT TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI BOONRAY INTELLIGENT TECH CO LTD
Filing Date
2026-03-05
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing unmanned mining truck battery swapping route planning technology lacks comprehensive consideration of multiple factors such as actual working conditions in the mining area, power status, traffic dynamics, and battery swapping station load. This leads to unreasonable battery swapping route planning and frequent scheduling conflicts, making it difficult to avoid resource competition and route congestion, thus affecting the efficiency and operational continuity of the overall transportation system.

Method used

By acquiring the real-time location and power information of unmanned mining vehicles, and combining multi-dimensional dynamic factors such as path length, time, power consumption, number of available batteries, and queuing status of each battery swapping station, a cost score is constructed and the battery swapping waiting time is predicted. An improved Hybrid A* path planning algorithm and trajectory optimization algorithm are used to generate the optimal battery swapping task route, thereby optimizing the battery swapping path and scheduling decisions.

Benefits of technology

It enables refined evaluation and dynamic optimization of battery swapping routes, improves the rationality of route planning and the accuracy of scheduling decisions, enhances the coordination and orderliness of multi-vehicle battery swapping processes, alleviates resource competition and route congestion, and improves the overall operational efficiency and continuity of the transportation system.

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Abstract

The application relates to a route planning method and system for battery replacement of an unmanned mine car, and belongs to the technical field of route planning. The method comprises the following steps: acquiring position information and battery capacity information of the unmanned mine car; when the residual capacity of the mine car is less than a preset residual capacity; calculating path lengths, time consumption and power consumption of the mine car from a current position to positions of various battery replacement stations; calculating cost scores of the various battery replacement stations, and determining a candidate battery replacement station set based on the cost scores; predicting battery replacement waiting times of the mine car at the various candidate battery replacement stations based on the time consumption, the number of available batteries of the various candidate battery replacement stations, queuing queue data and battery capacity completion times; determining an optimal battery replacement station based on the cost scores and the battery replacement waiting times; generating a battery replacement task route of the unmanned mine car based on the optimal battery replacement station through a trajectory optimization algorithm; and controlling the unmanned mine car to drive into the optimal battery replacement station for battery replacement, and re-entering the planning process.
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