Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots

TL;DR

This paper presents a fully autonomous quadrotor system equipped with onboard 3D lidar and computing that can detect and avoid small, dynamic obstacles in cluttered environments at real-time speeds.

Contribution

The authors develop an integrated onboard sensing and planning system enabling quadrotors to avoid small and dynamic obstacles using real-time perception and kinodynamic planning.

Findings

Successfully avoids obstacles as small as 20mm in diameter.

Operates onboard at 50Hz for perception and planning.

Demonstrates safe navigation in cluttered indoor and outdoor environments.

Abstract

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 50Hz with careful optimization. Various indoor and outdoor experiments show that the system can avoid dynamic small obstacles (down to 20mm diameter bar) while flying at 2m/s in cluttered environments. Our codes and hardware design are open-sourced on Github.