  This paper presents a multi-robot kinodynamic motion planner that enables a
team of robots with different dynamics, actuation limits, and shapes to reach
their goals in challenging environments. We solve this problem by combining
Conflict-Based Search (CBS), a multi-agent path finding method, and
discontinuity-bounded A*, a single-robot kinodynamic motion planner. Our
method, db-CBS, operates in three levels. Initially, we compute trajectories
for individual robots using a graph search that allows bounded discontinuities
between precomputed motion primitives. The second level identifies inter-robot
collisions and resolves them by imposing constraints on the first level. The
third and final level uses the resulting solution with discontinuities as an
initial guess for a joint space trajectory optimization. The procedure is
repeated with a reduced discontinuity bound. Our approach is anytime,
probabilistically complete, asymptotically optimal, and finds near-optimal
solutions quickly. Experimental results with robot dynamics such as unicycle,
double integrator, and car with trailer in different settings show that our
method is capable of solving challenging tasks with a higher success rate and
lower cost than the existing state-of-the-art.
