Tactical AGENTFLY is an ongoing U.S. Army-sponsored research project developing agent-based coordination and planning techniques for multi-UAV information collection missions with special emphasis on complex urban environments.
Unmanned aerial vehicles (UAVs) have been increasingly deployed for aerial surveillance. The present UAVs are able to perform most of their flight control level tasks autonomously and there is a strong demand for intelligent systems providing an interface for high-level commands. The project aims to provide such high-level control, allowing the operator to communicate with a fleet of UAVs on a high level in terms of collection tasks and their results, with detailed allocation of the tasks to individuals UAVs and planning of their optimum trajectories performed automatically. The following basic information collection tasks are supported:
In both cases, the control algorithms have to respect UAV’s flight model constraints, sensory constraints and maintain collision-free trajectories. The development of such robust and effective multi-agent control mechanisms for the individual information tasks is an important objective of the project. The ultimate objective, however, is the development of methods that can efficiently and autonomously address heterogeneous combinations of the basic tasks (termed mixed information collection). The primary performance metric is the difference between the true state of the tracked targets/area and the state reported by the UAVs employing the proposed control mechanisms. All metrics are evaluated both on synthetic experiments and on a realistic simulation of a search-and-capture operation in a complex urban environment.
The project has been producing a number of results of formal, algorithmic and software nature. Specifically, we have developed and are continuously extending the following:
All developed component are integrated with the Core AGENTFLY technology providing support for the base UAV functionality (detailed simulation of UAV in-flight operation, optimized flight path planner respecting aircraft’s physical constraints, robust decentralized utility-based collision avoidance mechanisms etc.)
Dr. Michal Pechoucek (principal investigator), Dr. Michal Jakob (project leader), Eduard Semsch, Dusan Pavlicek and Vojtech Elias (team members)