Robust collision avoidance for multiple micro aerial vehicles using nonlinear model predictive control

When several Multirotor Micro Aerial Vehicles (MAVs) share the same airspace, reliable and robust collision avoidance is required. In this paper we address the problem of multi-MAV reactive collision avoidance. We employ a model-based controller to simultaneously track a reference trajectory and avoid collisions. Moreover, to achieve a higher degree of robustness, our method also accounts for the uncertainty of the state estimator and of the position and velocity of the other agents. The proposed approach is decentralized, does not require a collision-free reference trajectory and accounts for the full MAV dynamics. We validated our approach in simulation and experimentally with two MAV.

Authors

• Mina Kamel 0001
• Javier Alonso-Mora
• Roland Siegwart
• Juan I. Nieto 0001

Keywords

• Collision avoidance
• Trajectory
• Cost function
• Trajectory tracking
• Robustness
• Vehicle dynamics
• Aerial Vehicles
• Model Predictive Control
• Nonlinear Control
• Nonlinear Model Predictive Control
• Micro Air Vehicles
• Reference Trajectory
• Position Of Agent
• Velocity Of Agent
• Collision-free Trajectory
• Optimization Problem
• System Dynamics
• Control Input
• Angular Velocity
• Error Propagation
• Inertial Measurement Unit
• Core I7
• Tracking Control
• Optimal Control Problem
• Prediction Horizon
• Trajectory Tracking Control
• Hard Constraints
• Robot Operating System
• Sequential Quadratic Programming
• Trajectory Generation
• Inertial Frame
• Control Formulation
• Clock Synchronization
• Trajectories Of Agents
• Pitch Angle