A Sampling-Based Tree Planner for Robot Navigation Among Movable Obstacles
Nicola Castaman, Elisa Tosello, Enrico Pagello · International Symposium on Robotics · 2016
This thesis proposes a planner that solves Navigation Among Movable Obstacles problems giving robots the ability to reason about the environment and choose when manipulating obstacles. The planner combines the A*-Search and the exploration strategy of the Kinodynamic Motion Planning by Interior-Exterior Cell Exploration algorithm. It is locally optimal and independent from the size of the map and from the number, shape, and position of obstacles. It assumes full world knowledge