Description
Multi-Vehicle Health Management by Josh Redding and Brett Bethke
Coordinated multi-vehicle autonomous systems have the potential to provide incredible functionality, but off-nominal conditions and degraded system components can render this capability ineffective. This research effort is focused on developing techniques to improve mission-level functional
reliability through better system self-awareness and adaptive mission planning. This extends the
traditional definition of health management, which has historically referred to the process of actively
monitoring and managing vehicle sub-systems (e.g., avionics) in the event of component failures, to
the context of multiple vehicle operations and autonomous multi-agent teams. In this case, health
management information about each mission system component is used to improve the mission
system's self-awareness and adapt vehicle, guidance, task and mission plans. As discussed in the
following, the focus of our work has been on establishing the theoretical foundations of health-aware
task planning, developing tractable solution algorithms to the resulting optimizations, and using a
unique multi-UAV testbed called RAVEN to experimentally demonstrate the benefits of the new
approach.
