Path planning, the art of finding a way from point ’A’ to point ’B’ is well researched in the field of robotics, but there are still challenges to address. In this thesis you will work on the expansion of the path planner called D*+, that is based on a D* lite planning library, to address the issue of large amount of memory usage and heavy computations, asthe map expands when deployed in large environments. The main core of the proposal is to integrate the UFOMap (or similar), an octree‐based probabilistic mapping, in the current planning framework, for faster re‐planning and less memory consumption.

• The task is to implement a D* path planner library that works directly on an octree map.

• Variation of D* planner should be selected based on performance.

• If  UFOMap or another octree‐based mapper to used, it will be decided based on state of art.

• Knowledge in C++ will be needed.

• Experience with code optimization is good but not necessarily.

• The participant has a weekly discussion with her/his supervisor in order to be guided.