Robot Manipulation of Human Tools: Autonomous Detection and Control of Task Relevant Features

The efficient acquisition and generalization of skills for manual tasks requires that a robot be able to perceive and control the important aspects of an object while ignoring irrelevant factors. For many tasks involving everyday toollike objects, detection and control of the distal end of the object is sufficient for its use. For example, a robot could pour a substance from a bottle by controlling the position and orientation of the mouth. Likewise, the canonical tasks associated with a screwdriver, hammer, or pen rely on control of the tool’s tip. In this paper, we present methods that allow a robot to autonomously detect and control the tip of a tool-like object. We also show results for modeling the appearance of this important type of task relevant feature. 1