Nonlinear Model Predictive Control for Multi-Micro Aerial Vehicle Robust Collision Avoidance
This work addresses collision avoidance for multi-MAV systems, which is an incremental improvement by incorporating robustness to uncertainties in a decentralized manner.
The paper tackled the problem of reactive collision avoidance for multiple micro aerial vehicles (MAVs) sharing airspace, achieving simultaneous reference trajectory tracking and collision avoidance with robustness to uncertainties in state estimation and other agents' positions and velocities.
Multiple multirotor Micro Aerial Vehicles sharing the same airspace require a reliable and robust collision avoidance technique. In this paper we address the problem of multi-MAV reactive collision avoidance. A model-based controller is employed to achieve simultaneously reference trajectory tracking and collision avoidance. Moreover, we also account for the uncertainty of the state estimator and the other agents position and velocity uncertainties to achieve a higher degree of robustness. The proposed approach is decentralized, does not require collision-free reference trajectory and accounts for the full MAV dynamics. We validated our approach in simulation and experimentally.