A Cooperative Hunting Algorithm of Multi-robot Based on Dynamic Prediction of the Target via Consensus-based Kalman Filtering

Abstract

Aiming to the problem of the unknown trajectory for the target robot which escapes on its own initiative, a multi-robot collaborated hunting algorithm is proposed based on dynamic prediction of the target in dynamic environment. Firstly, sample points of the target robot are updated to fit its trajectories and the consensus based on Consensus-based Kalman Filtering is further used to dynamically predict the position of the target. Secondly, the appropriate hunting points are distributed for the pursuit robots by the particle swarm optimization algorithm. The pursuit robots surround the target robot and constantly narrow the encirclement so that they finish the task. The simulation results show that the proposed algorithm is feasible and effective.