Reactive Receding Horizon Planning and Control for Quadrotors with Limited On-Board Sensing

Abstract

The paper presents a receding horizon planning strategy for a quadrotor-type mav to navigate through an unknown cluttered environment at high speed. Utilizing a lightweight on-board short-range sensor that generates point-clouds within a narrow Field of View (FOV), the reported approach generates safe and dynamically feasible trajectories within the fov of the sensor, which the mav uses to navigate without relying on any global planner or prior information about the environment. The effectiveness of this planner-controller combination is demonstrated in both indoor and outdoor tests featuring speeds of up to of 3.5 m/s. With minor adjustments, the local motion planner can be utilized for interception and tracking of a moving target; evidence to this effect are provided in the form of numerical (Gazebo) simulations. Given the absence of any global information about the robot's workspace, the extent to which the local planner can provide convergence guarantees is limited; when complemented by a global planner and/or target tracker, the reported lower-level, sensor-driven reactive motion control strategy completes the autonomous mav navigation stack, enabling navigation in dynamic, uncertain, and partially-known environments with guaranteed convergence to any static or dynamic target.