Multi-mobile-robot obstacle avoidance control method based on dynamic control obstacle function

By preprocessing and elliptic parameterization of dynamic obstacle point clouds, and combining continuous frame data for state prediction and responsibility allocation, dynamic control obstacle function constraints are constructed. This solves the problems of inaccurate obstacle modeling and unreasonable task allocation in obstacle avoidance for multiple mobile robots, and achieves stable formation and safe obstacle avoidance.

CN122363307APending Publication Date: 2026-07-10ZHEJIANG UNIV OF TECH
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Patent Information

Application Number
CN202610739685.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-27
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing obstacle avoidance methods for multiple mobile robots suffer from inaccurate obstacle boundary modeling, insufficient utilization of dynamic obstacle movement trends, inadequate prediction error safety margins, and unreasonable allocation of obstacle avoidance tasks among different robots, leading to unstable formation motion and insufficient safety.

Method used

By preprocessing and clustering dynamic obstacle point cloud data, elliptical parameterized obstacles are fitted, and state estimation and future prediction are performed by combining continuous frame data. Discrete-time dynamic control obstacle function constraints are constructed, obstacle avoidance responsibility coefficient and formation keeping weight are dynamically adjusted, and a model predictive control optimization model is established.

Benefits of technology

Stable formation and safe obstacle avoidance of multiple mobile robots in dynamic obstacle environments were achieved, reducing the computational complexity of the controller, reducing obstacle avoidance response lag, improving safety margin, optimizing task allocation, and maintaining the stability and safety of the formation.

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Abstract

The invention relates to a multi-mobile-robot obstacle avoidance control method based on a dynamic control obstacle function. The multi-mobile-robot obstacle avoidance control method comprises the following steps that S1, state information of multiple mobile robots and dynamic obstacle point cloud data are obtained; s2, performing preprocessing to obtain a plurality of obstacle point cloud clusters; s3, performing ellipse parameterization fitting to obtain ellipse obstacle parameters; s4, obtaining an elliptical obstacle sequence in the prediction time domain based on the elliptical obstacle parameters; s5, obtaining an extended elliptical obstacle sequence; s6, establishing a formation reference model to generate a reference trajectory; s7, constructing a discrete time dynamic control barrier function constraint as a security constraint; s8, calculating an obstacle avoidance risk index and an obstacle avoidance responsibility coefficient, and adjusting a formation keeping weight and an obstacle avoidance constraint weight in model prediction control; and S9, establishing a model based on the adjusted weight, obtaining a prediction control input sequence, and performing rolling optimization. The method has the beneficial effects that the modeling accuracy, the motion trend utilization rate and the prediction error safety margin precision are improved.
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