Receding Horizons with Heading Constraints for Collision Avoidance

This paper shows an application of model predictive control with receding horizons for the cooperative control of unmanned aerial vehicles in unknown environments. Line of sight and range constrain the perceived environment. It is shown that the receding horizons can be divided into temporal and spatial horizons. The cooperative control problem investigated in this paper uses short spatial horizons and it is decentralized. A method is proposed and evaluated for collision avoidance between vehicles and with obstacles. Sample scenarios show the effectiveness of the proposed collision avoidance algorithm. Finally, it is shown that model predictive control with receding horizons can handle task allocation, path planning and trajectory generation in one completely unified method.

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