Collision avoidance is the primary problem to be solved in formation flight of multiple Unmanned aerial vehicles(UAVs). Firstly, a cooperative collision avoidance architecture of multiple UAVs is designed according to the requirement of autonomous collision avoidance of single UAV. Then a new cooperative collision avoidance method of multiple UAVs based on Kalman filter and model predictive control(MPC) is proposed. In this method, extended Kalman filter(EKF) is used to estimate the state of obstacles and target points in uncertain environment space, and to predict the trajectory of obstacles and target points. At the same time, relevant performance index functions and constraints are set up. On the basis of sharing environmental information, model predictive control strategy is used to guide and make cooperative collision avoidance decisions for multiple UAVs. The simulation results show that the proposed method is effective in uncertain environment perception and UAV collision avoidance, and the cooperative mechanism has obvious advantages.


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    Title :

    Cooperative Collision Avoidance Method for Multi-UAV Based on Kalman Filter and Model Predictive Control


    Contributors:
    Huang, Hanqiao (author) / Zhou, Huan (author) / Zheng, Meiyun (author) / Xu, Cheng (author) / Zhang, Xiaofeng (author) / Xiong, Wei (author)


    Publication date :

    2019-11-01


    Size :

    974815 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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