Speed-First: An Aggressive Gradient-Based Local Planner for Quadrotor Faster Flight

Autonomous flight for quadrotors is maturing with the development of real-time local trajectory planning. However, the current local planning method is too conservative to waste the agility of the quadrotors. So in this paper, we have focused on aggressive local trajectory planning and proposed a gradient-based planning method to rapidly plan faster executable trajectories while ensuring it is collision-free. A distance gradient information generation strategy is proposed, which finds a collision-free Hybrid-A* path to replace the control points in obstacles for safety and creates the distance gradient used in the back-end optimization. Besides, we present a novel and aggressive time span cost term to tackle unfeasibility and improve the overall trajectory speed. Extensive simulations and real-world experiments are tested to validate our method. The results show that our proposed method generates a more aggressive trajectory with a shorter planning time and a faster flight speed than the classical gradient-based method.