Human-Assisted RRT for Path Planning in Urban Environments

A human-RRT (Rapidly-exploring Random Tree) collaborative algorithm is presented for path planning in urban environments. The well-known RRT algorithm is modified for efficient planning in cluttered, yet structured urban environments. To engage the expert human knowledge in dynamic replanning of autonomous vehicles, a graphical user interface is developed that enables interaction with the automated RRT planner in real-time. The interface can be used to invoke standard planning attributes such as way areas, space constrains, and waypoints. In addition, the human can draw desired trajectories using the touch interface for the RRT planner to follow. Based on new information and evidence collected by human, state-dependent risk or penalty to grow paths based on an objective function can also be specified using the interface.