  Many applications involving complex multi-task problems such as disaster
relief, logistics and manufacturing necessitate the deployment and coordination
of heterogeneous multi-agent systems due to the sheer number of tasks that must
be executed simultaneously. A fundamental requirement for the successful
coordination of such systems is leveraging the specialization of each agent
within the team. This work presents a Receding Horizon Planning (RHP) framework
aimed at scheduling tasks for heterogeneous multi-agent teams in a robust
manner. In order to allow for the modular addition and removal of different
types of agents to the team, the proposed framework accounts for the
capabilities that each agent exhibits (e.g. quadrotors are agile and agnostic
to rough terrain but are not suited to transport heavy payloads). An
instantiation of the proposed RHP is developed and tested for a search and
rescue scenario. Moreover, we present an abstracted search and rescue
simulation environment, where a heterogeneous team of agents is deployed to
simultaneously explore the environment, find and rescue trapped victims, and
extinguish spreading fires as quickly as possible. We validate the
effectiveness of our approach through extensive simulations comparing the
presented framework with various planning horizons to a greedy task allocation
scheme.
