Using a group of robots in place of a single complex robot to accomplish a task has many benefits, including simplified system repair, less down time, and lower cost. Combining heterogeneous groups of these multi-robot systems allows addressing multiple subtasks in parallel, reducing the time it takes to address many problems, such as search and rescue, reconnaissance, and mine detection. These missions demand different roles for robots, necessitating a strategy for coordinated autonomy while respecting any constraints the environment may impose. Synthesis of control policies for heterogeneous multirobot systems is particularly challenging because of inter-robot constraints such as communication maintenance and collision avoidance, the need to coordinate robots within groups, and the dynamics of individual robots.
I will present approaches to synthesizing feedback policies for navigating groups of robots in constrained environments. These approaches automatically and concurrently solve both the path planning and control synthesis problems, and are specified at a high level, for example, using an iPad interface to navigate a complex environment with a team of UAVs. I will also present some preliminary work on novel approaches to developing controllers for many types of multirobot tasks, by using crowdsourced multi-player game data.