Visual Servoing of Micro Aerial Vehicles with the Cooperation of Ground Vehicle

A ground-to-air cooperation system is proposed in this article aiming to enhance the performance of Micro Aerial Vehicles(MAVs) in GPS-denied environment. The MAV cooperates with the ground vehicle to complete flying task. Specifically, the ground vehicle uses a monocular camera to track the marker points on the MAV with background subtraction and optical flow algorithms to avoid interference from unrelated backgrounds, and calculates the position relative to the ground vehicle. After receiving the position of the ground vehicle, the MAV fuses the observed position with its own accelerometer information, and performs self-state estimation and feedback control. Compared with the past methods, the proposed method can effectively remove the interference of complex background, perform point-tracking on the MAV markers to improve the robustness of positioning, and reduce the state estimation delay by fusing multi-sensor information. Experiments are carried out to verify the flight path of the MAV observed by the ground vehicle with the trajectory from the Vicon motion capture system, and thus prove the accuracy and effectiveness of the system.

[1]  Z. Zivkovic Improved adaptive Gaussian mixture model for background subtraction , 2004, ICPR 2004.

[2]  Andreas Zell,et al.  Visual tracking and following of a quadrocopter by another quadrocopter , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Xiaohu Zhang,et al.  Multi-camera networks for motion parameter estimation of an aircraft , 2017 .

[4]  Andreas Zell,et al.  A Cross-Platform Comparison of Visual Marker Based Approaches for Autonomous Flight of Quadrocopters , 2013, Journal of Intelligent & Robotic Systems.

[5]  Pratap Tokekar,et al.  Sensor planning for a symbiotic UAV and UGV system for precision agriculture , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Giovanni Muscato,et al.  UAV/UGV cooperation for surveying operations in humanitarian demining , 2013, 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

[7]  Ivan Roselli,et al.  Acoustic system for aircraft detection and tracking based on passive microphones arrays , 2004 .

[8]  Vijay Kumar,et al.  The GRASP Multiple Micro-UAV Testbed , 2010, IEEE Robotics & Automation Magazine.

[9]  Vijay Kumar,et al.  Opportunities and challenges with autonomous micro aerial vehicles , 2012, Int. J. Robotics Res..

[10]  Lucian Busoniu,et al.  Vision and Control for UAVs: A Survey of General Methods and of Inexpensive Platforms for Infrastructure Inspection , 2015, Sensors.

[11]  Gang Chen,et al.  Design and Development of a Multi-rotor Unmanned Aerial Vehicle System for Bridge Inspection , 2016, ICIRA.

[12]  Jörg Stückler,et al.  Multilayered Mapping and Navigation for Autonomous Micro Aerial Vehicles , 2016, J. Field Robotics.