  We present an approach that generates kinodynamically feasible paths for
robots using Rapidly-exploring Random Tree (RRT). We leverage motion primitives
as a way to capture the dynamics of the robot and use these motion primitives
to build branches of the tree with RRT. Since every branch is built using the
robot's motion primitives that doesn't lead to collision with obstacles, the
resulting path is guaranteed to satisfy the robot's kinodynamic constraints and
thus be feasible for navigation without any post-processing on the generated
trajectory. We demonstrate the effectiveness of our approach in simulated 2D
environments using simple robot models with a variety of motion primitives.
