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An efficient subspace approach is used to find collision-free paths in congested workspaces for a general class of robots having revolute and/or prismatic joints. A three-dimensional joint space is formed by mapping the workspace obstacles represented by polyhedral elements into the robot’s primary degrees-of-freedom comprising the first three robot links, also modeled by polyhedral elements. In this approach the secondary degrees-of-freedom (>3), including objects grasped by the robot end-effector, are bounded by a box attached to the distal primary link. The joint space obstacles represent forbidden space that limits the allowable robot configurations. Paths are then planned on a two-dimensional direct subspace of the joint space using graphics cursor input. Methods of iteration elimination are used to reduce the computational time required to transform obstacles into the joint space.

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SUMMARYMinimum distance algorithms allow users of robot simulation programs to maneuver manipulation arms around and between workspace obstacles. Additionally, they can be used to generate configuration maps for path planning of the manipulator “point” through a more abstract configuration space. This paper summarizes an algorithm for determining minimum distances between two polyhedral elements. Examples of configuration space maps and Cartesian stepping techniques demonstrate algorithmic utility for robot path planning. A number of accelerating strategies which depend on a heirarchical spatial representation of manipulator and workspace elements maintain reasonable CPU times for the simulation user.