  Given a heterogeneous group of robots executing a complex task represented in
Linear Temporal Logic, and a new set of tasks for the group, we define the task
update problem and propose a framework for automatically updating individual
robot tasks given their respective existing tasks and capabilities. Our
heuristic, token-based, conflict resolution task allocation algorithm generates
a near-optimal assignment for the new task. We demonstrate the scalability of
our approach through simulations of multi-robot tasks.
