Robot Path Planning

This thesis consists of three papers concerned with the basic path planning problem for robots moving in a known static environment. Our main interest has been industrial robots, but the methods are general and apply to a wide range of robots. The path planning problem is to find a sequence of configurations that moves a robot from an initial configuration to a goal configuration without colliding with obstacles in the environment. <p />The first paper presents a variation of the Probabilistic Roadmap Method (PRM). The new planner is called Lazy PRM and is tailored for single query path planning. By introducing a scheme for lazy evaluation, the pronounced multiple query planner is converted into an efficient single query planner. <p />The second paper presents a resolution complete, de-randomized version of Lazy PRM. The planner uses an implicit, non-uniform grid that allows local refinement to represent the configuration space. <p />The third paper presents a novel potential field method for free-flying rigid bodies. The planning is performed directly in the group <I>SE</I>(3) and is reinforced by a potential function in theR workspace. Thus, the planner benefits from the explicit representation of the workspace obstacles at the same time as the planning takes place in the 6-dimensional configuration space. The potential function is harmonic and is composed of translates of the Green kernel in <I>SE</I>(3). <p />Experimental results provided show that the planners are capable of solving relevant problems in various environments