A search algorithm for motion planning with six degrees of freedom

The motion planning problem is of central importance to the fields of robotics, spatial planning, and automated design. In robotics we are interested in the automatic synthesis of robot motions, given high-level specifications of tasks and geometric models of the robot and obstacles. The “Movers'” problem is to find a continuous, collision-free path for a moving object through an environment containing obstacles. We present an implemented algorithm for the classical formulation of the three-dimensional Movers' problem: Given an arbitrary rigid polyhedral moving object P with three translational and three rotational degrees of freedom, find a continuous, collision-free path taking P from some initial configuration to a desired goal configuration.This paper describes an implementation of a complete algorithm (at a given resolution) for the full six degree of freedom Movers' problem. The algorithm transforms the six degree of freedom planning problem into a point navigation problem in a six-dimensional configuration space (called C-space). The C-space obstacles, which characterize the physically unachievable configurations, are directly represented by six-dimensional manifolds whose boundaries are five-dimensional C-surfaces. By characterizing these surfaces and their intersections, collision-free paths may be found by the closure of three operators which (i) slide along five-dimensional level C-surfaces parallel to C-space obstacles; (ii) slide along one- to four-dimensional intersections of level C-surfaces; and (iii) jump between six-dimensional obstacles. These operators are employed by a best-first search algorithm in C-space. We will discuss theoretical properties of the algorithm, including completeness (at a resolution). This paper describes the heuristic search, with particular emphasis on the heuristic strategies that evaluate local geometric information. At the heart of this paper lie the design and implementation of these strategies for planning paths along level C-surfaces and their intersection manifolds, and for reasoning about motions with three degrees of rotational freedom. The problems of controlling the interaction of these strategies, and of integrating diverse local experts for geometric reasoning provide an interesting application of search to a difficult domain with significant practical implications. The representations and algorithms we develop impact many geometric planning problems, and extend to Cartesian manipulators with six degrees of freedom.