Time-Continuous Real-Time Trajectory Generation for Safe Autonomous Flight of a Quadrotor in Unknown Environment

Abstract

In this paper, we present an efficient global and local replanning method for a quadrotor to complete a flight mission in a cluttered and unmapped environment. A minimum-snap global path planner generates a global trajectory that comprises some waypoints in a cluttered environment. When facing unexpected obstacles, our method modifies the global trajectory using geometrical planning and closed-form formulation for an analytical solution with 9th-order polynomial. The proposed method provides an analytical solution, not a numerical one, and it is computationally efficient without falling into a local minima problem. In a simulation, we show that the proposed method can fly a quadrotor faster than the numerical method in a cluttered environment. Furthermore, we show in experiments that the proposed method can provide safer and faster trajectory generation than the numerical method in a real environment.