COUNTER Cooperative Control Algorithms: Challenges and Lessons Learned
Steven Rasmussen, Michael Holland, Adam Bry · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2008
As part of the COUNTER program, cooperative control algorithms have been designed, implemented, and tested. This paper describes challenges, and their solutions, that were encountered during the program. The cooperative control challenges include: system configuration, suitability of the algorithms, and algorithm implementation into the system. During flight tests challenges arose such as: selection of autopilot, generation of flyable trajectories, and ability to image targets. In order to advance the state-of-the-art of Intelligence Surveillance and Reconnaissance (ISR) using Unmanned Aerial Vehicles (UAVs) over urban areas, researchers from the Air Force Research Laboratory conducted a project called Cooperative Operations in UrbaN TERrain (COUNTER). COUNTER consists of basic research, algorithm and ground station development, and flight tests. The concept employed in COUNTER is operator-on-the-loop control of Small unmanned Aerial Vehicles (SAVs) and Micro unmanned Aerial Vehicles (MAVs) performing cooperative multilevel ISR. In this concept, a single ground operator controls a single SAV, that flies high enough to view large portions of the urban area, and a team of four MAVs, that fly low enough to get good resolution images of objects selected from the SAV video. For an overview of the COUNTER program, see Jodeh 2008. 1 Since this program has included everything from concept to flight test, there were many conceptual and practical challenges to overcome. These challenges can be separated into two categories: those involving the cooperative control algorithms, and those involving vehicle control. The remainder of this paper provides an overview of the challenges that were encountered, explains how they were resolved, and discusses the lessons learned during the project.