Collision/Obstacle Avoidance Cooperative Tracking Control for MASs With Network Constraints

In this article, the collision/obstacle avoidance cooperative control problem for nonlinear multiagent systems (MASs) with network constraints is investigated. Under network constraints, the speed at which agents make cooperative decisions is constrained, thereby increasing the risk of collisions. A distributed command governor is given, which intelligently adjusts the reference signals of agents in combination with the communication performance. When facing interagent collisions, a spatially looser formation shape is generated. When facing obstacles, a safe command signal is searched via an artificial potential field-like method to ensure that there are no collisions between two agents and between agents and obstacles. It is shown that the agents can bypass the obstacles in flexible formation and quickly recover the desired formation shape after bypassing the obstacles. Finally, the simulation and experiment of nonholonomic mobile robots verify the effectiveness and the advantages of the proposed scheme.

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Publication Details

Journal
IEEE Transactions on Control Systems Technology
Published
2025-09-26
DOI
https://doi.org/10.1109/tcst.2025.3610917
Citations
1
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
2.48
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article

Collision/Obstacle Avoidance Cooperative Tracking Control for MASs With Network Constraints

1 citations
IEEE Transactions on Control Systems Technology
Geochemistry and Geologic Mapping
2.48
article

Collision/Obstacle Avoidance Cooperative Tracking Control for MASs With Network Constraints

article en
1 citations

Abstract

In this article, the collision/obstacle avoidance cooperative control problem for nonlinear multiagent systems (MASs) with network constraints is investigated. Under network constraints, the speed at which agents make cooperative decisions is constrained, thereby increasing the risk of collisions. A distributed command governor is given, which intelligently adjusts the reference signals of agents in combination with the communication performance. When facing interagent collisions, a spatially looser formation shape is generated. When facing obstacles, a safe command signal is searched via an artificial potential field-like method to ensure that there are no collisions between two agents and between agents and obstacles. It is shown that the agents can bypass the obstacles in flexible formation and quickly recover the desired formation shape after bypassing the obstacles. Finally, the simulation and experiment of nonholonomic mobile robots verify the effectiveness and the advantages of the proposed scheme.

IEEE Transactions on Control Systems TechnologyVol. 34(1)
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University (CN)
Reduced inequalities
Openalex Percentile: Top 7%
Geochemistry and Geologic Mapping
2.48
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