  Avoiding collisions is one of the vital tasks for systems of autonomous
mobile agents. We focus on the problem of finding continuous coordinated paths
for multiple mobile disc agents in a 2-d environment with polygonal obstacles.
The problem is PSPACE-hard, with the state space growing exponentially in the
number of agents. Therefore, the state of the art methods include mainly
reactive techniques and sampling-based iterative algorithms.
  We compare the performance of a widely-used reactive method ORCA with three
variants of a popular planning algorithm RRT* applied to multi-agent path
planning and find that an algorithm combining reactive collision avoidance and
RRT* planning, which we call ORCA-RRT* can be used to solve instances that are
out of the reach of either of the techniques. We experimentally show that: 1)
the reactive part of the algorithm can efficiently solve many multi-agent path
finding problems involving large number of agents, for which RRT* algorithm is
often unable to find a solution in limited time and 2) the planning component
of the algorithm is able to solve many instances containing local minima, where
reactive techniques typically fail.
