Manipulation with Multiple Action Types

Abstract

We present DARRT, a sampling-based algorithm for planning with multiple types of manipulation. Given a robot, a set of movable objects, and a set of actions for manipulating the objects, DARRT returns a sequence of manipulation actions that move the robot and objects from an initial configuration to a final configuration. The manipulation actions may be non-prehensile, meaning that the object is not rigidly attached to the robot, such as push, tilt, or pull. We describe a simple extension to the RRT algorithm to search the combined space of robot and objects and present an implementation of DARRT on the Willow Garage PR2 robot.