Visual Tool Tip Detection and Position Estimation for Robotic Manipulation of Unknown Human Tools
Robots that use human tools could more easily work with people, perform tasks that are important to people, and bene t from human strategies for accomplishing these tasks. For a wide variety of tools and tasks, control of the tool's endpoint is su cient for its use. In this paper we present a straight-forward method for rapidly detecting the endpoint of an unmodeled tool and estimating its position with respect to the robot's hand. The robot rotates the tool while using optical ow to detect the most rapidly moving image points, and then nds the 3D position with respect to its hand that best explains these noisy 2D detections. The resulting 3D position estimate allows the robot to control the position of the tool endpoint and predict its visual location. We show successful results for this method using a humanoid robot with a variety of traditional tools, including a pen, a hammer, and pliers, as well as more general tools such as a bottle and the robot's own nger.1