Decentralized Multi-UAV Flight Autonomy for Moving Convoys Search and Track

This brief is concerned with integrated autonomous takeoff, target search, task assignment, and tracking using multiple fixed-wing unmanned aerial vehicles (UAVs) in urban environments. The problem is to design flight autonomy that is embedded onboard each UAV to enable autonomous flight coordination and distributed tasking. Control logic design based on a finite state automaton model, integrating four modes of operations, namely, the takeoff mode, the fly-to-area of operation mode, the search mode, and the tracking mode, is presented. Different from the state-of-the-art of recent research, this brief provides a preliminary research on the autonomous cooperative takeoff for miniature fixed-wing UAVs, by considering collision avoidance, communication failure, etc. To make UAVs autonomously and cooperatively search roads in the urban environments, an efficient improved search algorithm is proposed based on recent research on the coverage search in the literature. For the target tracking, using geometric relations (relative position, orientations, speed ratio, and minimal turning radius), a systematic algorithm is developed to generate an optimal online path. All the algorithms in this work are developed based on realistic miniature fixed-wing UAV dynamic models. The main focus of the brief is to test the developed control logic and also the algorithms. The proposed framework is evaluated by our 3-D multi-UAV test bed.

[1]  Lihua Xie,et al.  Integrated multi-agent system framework: decentralised search, tasking and tracking , 2015 .

[2]  Daniel J. Pack,et al.  Optimal path planning of a target-following fixed-wing UAV using sequential decision processes , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Lihua Xie,et al.  HNMSim: A 3D multi-purpose hybrid networked multi-agent simulator , 2012, Proceedings of the 31st Chinese Control Conference.

[4]  Kai-Yew Lum,et al.  Multiagent Information Fusion and Cooperative Control in Target Search , 2013, IEEE Transactions on Control Systems Technology.

[5]  Hugh F. Durrant-Whyte,et al.  Recursive Bayesian search-and-tracking using coordinated uavs for lost targets , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[6]  X. Rong Li,et al.  UAV Route Planning for Joint Search and Track Missions—An Information-Value Approach , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[7]  W. Grossman,et al.  Autonomous Searching and Tracking of a River using an UAV , 2007, 2007 American Control Conference.

[8]  Fredrik Gustafsson,et al.  Road Target Search and Tracking with Gimballed Vision Sensor on an Unmanned Aerial Vehicle , 2012, Remote. Sens..

[9]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[10]  Randal W. Beard,et al.  Cooperative Path Planning for Target Tracking in Urban Environments Using Unmanned Air and Ground Vehicles , 2015, IEEE/ASME Transactions on Mechatronics.

[11]  David Harel,et al.  Statecharts: A Visual Formalism for Complex Systems , 1987, Sci. Comput. Program..

[12]  Zhirong He,et al.  On trackability of a moving target by fixed-wing UAV using geometric approach , 2014, 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE).

[13]  Edwin K. P. Chong,et al.  Dynamic UAV path planning for multitarget tracking , 2012, 2012 American Control Conference (ACC).

[14]  Yue Wang,et al.  Awareness coverage control over large scale domains with intermittent communications , 2008, 2008 American Control Conference.

[15]  Lihua Xie,et al.  Decentralized search, tasking and tracking using multiple fixed-wing miniature UAVs , 2014, 11th IEEE International Conference on Control & Automation (ICCA).