Flight Testing a Heterogeneous Multi-UAV System with Human Supervision

Abstract

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 maximizing 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 flight test trials successfully accomplished the mission objectives. 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 allocation and path planning churning were observed which are linked to uncertainties of operating outdoors. Lessons learned during flight test operations are highlighted as they are relevant to other similar types of systems and missions.

Real-time dynamic planning to maintain network connectivity in a team of unmanned air vehicles

“…The CBBA algorithm runs in polynomial time, and has demonstrated good scalability with increasing numbers of agents and tasks. It has been demonstrated in numerous applications with teams of heterogeneous unmanned systems [13].…”

“…Each vehicle is 2.5 lbs, has a flight endurance of 18 minutes, and is capable of GPS waypoint navigation while communicating with the Ground Control Station (GCS) using a Digi-Mesh XBee 2.4 GHz radio module. The 3 UAV distributed system was in part integrated with the Aurora Flight Sciences multivehicle control framework which was recently developed and demonstrated to control 4 heterogeneous UAVs executing a complex mission using CBBA planning under human supervision [13]. Here, the system architecture seen in Figure 2 (c) consisted of several software modules communicating via the Lightweight Communications and Marshaling (LCM) UDP multicast protocol [14].…”

Mixed-initiative strategies for real-time scheduling of multiple unmanned vehicles

“…OPS-USERS was also adapted to operate with real UVs in an uncontrolled, outdoor environment [26]. The purpose of the effort was to demonstrate the technology in the context of a real-world operational scenario and to incorporate design elements into the system to make it robust to unpredictable hardware failures.…”

Mental Workload Assessment for UAV Traffic Control Using Consumer-Grade BCI Equipment

“…In recent years, the unmanned aerial vehicle (UAV) applications domain has seen a rapid growing interest in the development of systems able to assist human beings in critical operations [1][2][3]. Examples of such applications include security and surveillance, monitoring, search and rescue, disaster management, etc.…”