Cooperative Autonomous Tunnel Mapping

While unmanned air vehicles are starting to operate in complex urban and indoor environments, many challenges still remain. Our proposed project will address three key challenges through the development of algorithms. First, we reduce operator workload in the operation of autonomous vehicles in GPS denied environments. Second, the algorithms enable cooperative exploration by multiple and possibly heterogeneous agents. Third, the algorithms will maximize the searchable area in minimal time. The algorithms will be robust so that the team can operate without the need for constant communication. Performance is expected to degrade gracefully when agents spend an increasing amount of time without contact with each other. In Phase I we will develop software simulations to test and validate the cooperative control of multiple agents in performing search through a network of nodes. We will gain significant leverage from existing software in state estimation and mapping that can be used as a base to validate cooperative control. In Phase II we expect to be able to deploy a full team of autonomous flying vehicles performing exploration, mapping, and search. The team consists of members very skilled in the state of the art in estimation, mapping as well as coordination of multi-agents performing search.