Fast Time-optimal Avoidance of Moving Obstacles for High-Speed MAV Flight
This addresses the challenge of sudden obstacle avoidance during high-speed MAV flight, though it appears incremental as it builds on existing trajectory planning methods.
The paper tackles the problem of computing smooth, time-optimal trajectories for micro aerial vehicles (MAVs) to evade moving obstacles, achieving minimal computational demands that allow obstacle avoidance to begin within few milliseconds.
In this work, we propose a method to efficiently compute smooth, time-optimal trajectories for micro aerial vehicles (MAVs) evading a moving obstacle. Our approach first computes an n-dimensional trajectory from the start- to an arbitrary target state including position, velocity and acceleration. It respects input- and state-constraints and is thus dynamically feasible. The trajectory is then efficiently checked for collisions, exploiting the piecewise polynomial formulation. If collisions occur, viastates are inserted into the trajectory to circumvent the obstacle and still maintain time-optimality. These viastates are described by position, velocity, and acceleration. The evaluation shows that the computational demands of the proposed method are minimal such that obstacle avoidance can begin within few milliseconds. Optimality of generated trajectories, combined with the ability for frequent online re-planning from non-hover initial conditions, make the approach well suited for evasion of suddenly perceived obstacles during fast flight.