Path planning and obstacle avoidance system of unmanned logistics vehicle

By employing multi-objective optimization path planning algorithms and modular design, combined with adaptive weight allocation and Monte Carlo simulation algorithms, the path correction and obstacle avoidance problems of unmanned logistics vehicles under complex road conditions were solved, achieving accurate path adaptation and safe and efficient operation.

CN122131772APending Publication Date: 2026-06-02IND LEVEL 5G INNOVATION APPL (DALI) RES INST
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
IND LEVEL 5G INNOVATION APPL (DALI) RES INST
Filing Date
2026-04-09
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing path planning and obstacle avoidance technologies for autonomous logistics vehicles struggle to achieve precise path correction and dynamic adjustment under complex road conditions. Collision risk assessment is not accurate enough, and system module design is redundant or lacks coordination, resulting in poor path adaptability, low safety, and low operating efficiency.

Method used

A multi-objective optimization path planning algorithm is adopted, combined with adaptive weight allocation and Monte Carlo simulation algorithm, to generate real-time driving paths. Path correction and collision risk assessment are performed through environmental dynamic feature vectors. A hierarchical obstacle avoidance strategy is designed, and a modular system design is adopted to improve coordination and efficiency.

Benefits of technology

It achieves precise adaptation of path planning and obstacle avoidance systems in complex road conditions, reduces collision risks, improves operational efficiency and safety, and reduces system maintenance costs.

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Abstract

The application discloses a path planning and obstacle avoidance system of an unmanned logistics vehicle, and relates to the technical field of path planning, which comprises the following steps: acquiring real-time environment data; generating an initial optimal driving path optimized in multiple targets through a path planning algorithm; generating an environment dynamic characteristic vector; calculating path correction parameters based on the environment dynamic characteristic vector, correcting the initial optimal driving path according to the path correction parameters; determining a collision risk level according to the relative state of obstacles and the logistics vehicle; generating a corresponding obstacle avoidance strategy based on the collision risk level, generating a temporary obstacle avoidance path and triggering an obstacle avoidance execution instruction when the risk level reaches a preset threshold; and calculating a path deviation correction value and correcting the driving path. The application adopts a modular collaborative design corresponding to the whole process of path planning and obstacle avoidance, integrates dynamic path correction, accurate collision assessment, hierarchical obstacle avoidance and optimization heuristic function technology, and realizes efficient and safe collaborative control of path planning and obstacle avoidance of the unmanned logistics vehicle.
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