Temporal Logic Task Allocation in Heterogeneous Multirobot Systems

We consider the problem of optimally allocating tasks, expressed as global linear temporal logic (LTL) specifications, to teams heterogeneous mobile robots different types. Each task may require multiple To obtain a scalable solution, we propose hierarchical approach that first allocates specific tasks using information about contained in nondeterministic B $\ddot{\text{u}}$ chi automaton (NBA) captures LTL specification and then designs low-level paths for respect high-level assignment. Specifically, motivated by “lazy collision checking” methods robotics, prune relax NBA removing all negative atomic propositions, which simplifies planning checking constraint satisfaction only when needed. Then, extract sequences subtasks from relaxed along with their orders formulate mixed integer program allocate these robots. Finally, define generalized multirobot path problems satisfy both allocation constraints captured propositions original NBA. show our method is complete subclass covers broad range present numerical simulations demonstrating it can generate lower cost, considerably faster than existing methods.