Flight testing a heterogeneous multi-UAV system with human supervision
This paper presents the outdoor flight test results of a decentralized multi-UAV system supervised by a human operator. The system balances the roles of the human operator and the UAV autonomous behaviors with the objective of maxi- mizing the execution performance. The operator manages the mission by inputting and modifying tasks instead of controlling individual UAVs. The Consensus-Based Bundle Algorithm (CBBA) is used as a real-time, scalable, dynamic multi-agent multi-task planning algorithm to allocate tasks approved by the operator to UAVs. A team of three quadrotors and one fixed wing UAV collaborated in an operationally relevant scenario supporting a cargo UAV resupply mission. Thirteen of fourteen multi-UAV outdoor ight test trials successfully accomplished the mission objec- tives. The framework was shown to be robust to system failures and degradations commonly encountered during field testing primarily because of health monitoring and management tools that were incorporated in the design. Instances of task allo- cation and path planning churning were observed which are linked to uncertainties of operating outdoors. Lessons learned during ight test operations are highlighted as they are relevant to other similar types of systems and missions. ss© 2012 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
