Avoiding Dynamic Small Obstacles With Onboard Sensing and Computation on Aerial Robots

In practical applications, autonomous quadrotors are still facing significant challenges, such as the detection and avoidance of very small and even dynamic obstacles (e.g., tree branches, power lines). In this paper, we propose a compact, integrated, and fully autonomous quadrotor system, which can fly safely in cluttered environments while avoiding dynamic small obstacles. Our quadrotor platform is equipped with a forward-looking three-dimensional (3D) light detection and ranging (lidar) sensor to perceive the environment and an onboard embedded computer to perform all the estimation, mapping, and planning tasks. Specifically, the computer estimates the current pose of the UAV, maintains a local map (time-accumulated point clouds KD-Trees), and computes a safe trajectory using kinodynamic A* search to the goal point. The whole perception and planning system can run onboard at 50 Hz. Various indoor and outdoor experiments show that the system can avoid dynamic small obstacles (down to 9 mm diameter bar) while flying at 2 m/s in cluttered environments. High-speed experiments are also carried out, with a maximum speed of 5.5 m/s. Our codes are open-sourced on Github
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