Obstacle Avoidance via Hybrid Feedback
This work provides a guaranteed obstacle avoidance and stabilization method for autonomous navigation systems, which is an incremental improvement for robotics and control engineers.
This paper addresses the navigation problem of a point mass in n-dimensional space with ellipsoidal obstacles. The proposed hybrid control algorithm guarantees global asymptotic stabilization to a reference and obstacle avoidance, demonstrated through 2D and 3D simulations.
In this paper we present a hybrid feedback approach to solve the navigation problem of a point mass in the n-dimensional space containing an arbitrary number of ellipsoidal shape obstacles. The proposed hybrid control algorithm guarantees both global asymptotic stabilization to a reference and avoidance of the obstacles. The intuitive idea of the proposed hybrid feedback is to switch between two modes of control: stabilization and avoidance. The geometric construction of the flow and jump sets of the proposed hybrid controller, exploiting hysteresis regions, guarantees Zeno-free switching between the stabilization and the avoidance modes. Simulation results illustrate the performance of the proposed hybrid control approach for 2-dimensional and 3-dimensional scenarios.