Autonomous landing on a moving vehicle with an unmanned aerial vehicle
Abstract
This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year‐long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 04, 2019
- Source ID
- 10.1002/rob.21858
Entities
People
- Daniel Heřt
- Giuseppe Loianno
- Justin Thomas
- Martin Saska
- Petr Štěpán
- Robert Pěnička
- Tomáš Báča
- Vijay Kumar
- Vojtěch Spurný
Organizations
- Czech Science Foundation
- Czech Technical University in Prague
- Khalifa University
- New York University
- Office of Naval Research Global
- United States Army Research Laboratory
- University of Pennsylvania