The purpose of this research is to explore force constraints as a model of manipulator action. Robotic manipulation is usually modeled in terms of programmed motion-goals are specified as the motions of task objects, and robots are programmed by a sequence of arm motions. The programmed motion model works fairly well, provided that objects move only when rigidly grasped by the robot. However, many robot operations violate this assumption, manipulating objects without a rigid grasp. For example, when placing an object, the object may slip in the fingers. Or, when grasping an object, the object may be re-oriented and centered by pushing and squeezing. Other examples include striking, tilting, and the use of passive compliances. For these operations, and many others, the programmed motion model is awkward, because there is no direct transformation from desired object motions to robot motions. The research explores the use of task level force constraints, as an intermediate level model of action. A task level force constraint is any constraint on the force applied to a task object. For the operations where programmed motion is awkward, force constraints often provide a natural and effective way to transform desired object motions to corresponding robot commands. The approach is to build a planner, applying methods of classical mechanics to derive force constraints, and then using a variety of geometrical and analytical techniques to derive robots command parameters. Experimental evaluation will use a industrial manipulator and vision system to perform positioning and assembly tasks in a planar task domain.
