  We propose a generic multi-robot planning mechanism that combines an optimal
task planner and an optimal path planner to provide a scalable solution for
complex multi-robot planning problems. The Integrated planner, through the
interaction of the task planner and the path planner, produces optimal
collision-free trajectories for the robots. We illustrate our general algorithm
on an object pick-and-drop planning problem in a warehouse scenario where a
group of robots is entrusted with moving objects from one location to another
in the workspace. We solve the task planning problem by reducing it into an
SMT-solving problem and employing the highly advanced SMT solver Z3 to solve
it. To generate collision-free movement of the robots, we extend the
state-of-the-art algorithm Conflict Based Search with Precedence Constraints
with several domain-specific constraints. We evaluate our integrated task and
path planner extensively on various instances of the object pick-and-drop
planning problem and compare its performance with a state-of-the-art
multi-robot classical planner. Experimental results demonstrate that our
planning mechanism can deal with complex planning problems and outperforms a
state-of-the-art classical planner both in terms of computation time and the
quality of the generated plan.
