  Rapidly Exploring Random Trees (RRT) is one of the most widely used
algorithms for motion planning in the field of robotics. To reduce the
exploration time, RRT-Connect was introduced where two trees are simultaneously
formed and eventually connected. Probabilistic RRT used the concept of position
probability map to introduce goal biasing for faster convergence. In this
paper, we propose a modified method to combine the pRRT and RRT-Connect
techniques and obtain a feasible trajectory around the obstacles quickly.
Instead of forming a single tree from the start point to the destination point,
intermediate goal points are selected around the obstacles. Multiple trees are
formed to connect the start, destination, and intermediate goal points. These
partial trees are eventually connected to form an overall safe path around the
obstacles. The obtained path is tracked using an MPC + Stanley controller which
results in a trajectory with control commands at each time step. The
trajectories generated by the proposed methods are more optimal and in
accordance with human intuition. The algorithm is compared with the standard
RRT and pRRT for studying its relative performance.
