Fast autonomous landing on a moving target at MBZIRC

The ability to identify, follow, approach, and intercept a non-stationary target is a desirable capability of autonomous micro aerial vehicles (MAV) and puts high demands on reliable target perception, fast trajectory planning, and stable control. We present a fully autonomous MAV that lands on a planar platform mounted on a ground vehicle, relying only on onboard sensing and computing. We evaluate our system in simulation as well as with real robot experiments. Its resilience was demonstrated at the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) where it worked under competition conditions. Our team NimbRo ranked third in the MBZIRC Challenge 1 and — in combination with two other tasks — won the MBZIRC Grand Challenge.

[1]  Marcel Neuhausen,et al.  Park marking-based vehicle self-localization with a fisheye topview system , 2015, Journal of Real-Time Image Processing.

[2]  Daewon Lee,et al.  Autonomous landing of a VTOL UAV on a moving platform using image-based visual servoing , 2012, 2012 IEEE International Conference on Robotics and Automation.

[3]  Panos Marantos,et al.  Quadrotor landing on an inclined platform of a moving ground vehicle , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[4]  Tamir Tassa,et al.  Planning high order trajectories with general initial and final conditions and asymmetric bounds , 2014, Int. J. Robotics Res..

[5]  Sven Behnke,et al.  NimbRo Rescue: Solving Disaster‐response Tasks with the Mobile Manipulation Robot Momaro , 2017, J. Field Robotics.

[6]  Sven Behnke,et al.  Analytical time-optimal trajectory generation and control for multirotors , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[7]  Sven Behnke,et al.  A high-performance MAV for autonomous navigation in complex 3D environments , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[8]  Roland Siegwart,et al.  RotorS—A Modular Gazebo MAV Simulator Framework , 2016 .

[9]  Raffaello D'Andrea,et al.  A model predictive controller for quadrocopter state interception , 2013, 2013 European Control Conference (ECC).

[10]  Sven Behnke,et al.  NimbRo Rescue: Solving Disaster-Response Tasks through Mobile Manipulation Robot Momaro , 2018, ArXiv.

[11]  David Hyunchul Shim,et al.  Vision-based UAV landing on the moving vehicle , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[12]  Rita Cunha,et al.  Landing of a Quadrotor on a Moving Target Using Dynamic Image-Based Visual Servo Control , 2016, IEEE Transactions on Robotics.

[13]  Sven Behnke,et al.  Fast full state trajectory generation for multirotors , 2017, 2017 International Conference on Unmanned Aircraft Systems (ICUAS).

[14]  Raffaello D'Andrea,et al.  A computationally efficient algorithm for state-to-state quadrocopter trajectory generation and feasibility verification , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Jerome Le Ny,et al.  Autonomous Landing of a Multirotor Micro Air Vehicle on a High Velocity Ground Vehicle , 2016, ArXiv.