  This paper introduces a quadrotor's autonomous take-off and landing system on
a moving platform. The designed system addresses three challenging problems:
fast pose estimation, restricted external localization, and effective obstacle
avoidance. Specifically, first, we design a landing recognition and positioning
system based on the AruCo marker to help the quadrotor quickly calculate the
relative pose; second, we leverage a gradient-based local motion planner to
generate collision-free reference trajectories rapidly for the quadrotor;
third, we build an autonomous state machine that enables the quadrotor to
complete its take-off, tracking and landing tasks in full autonomy; finally, we
conduct experiments in simulated, real-world indoor and outdoor environments to
verify the system's effectiveness and demonstrate its potential.
