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A Visual Predictive Control Framework for Robust and Constrained Multi-Agent Formation Control
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AI
DOI：10.1007/s10846-022-01674-5.png)
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Abstract
En 中文
In this study, the problem of leader-follower position-based formation control is considered. Each agent in the multi-agent network is equipped with a perspective camera (assumed to be pinhole-type) and is servoed visually. A depth-based visual predictive controller is proposed. The framework optimizes the planned trajectory with a prediction horizon, while taking image- and physical-space constraints into account. Furthermore, the presented control scheme provides robustness against the camera occlusion, modeling errors and uncertainties. The performance of the proposed tracking algorithm is validated via numerous simulations.
Keywords:
Model predictive control
Visual servoing
Robotics
Discrete-time multi-agent systems
Journal
J
IF:
2.8
Papers:
3.8K
Citations:
6.9K