Bluethmann, W., R, Ambrose, M. Diftler, E. Huber, A, Fagg, M. Rosenstein, R. Platt, R. Grupen, C. Breazeal, A. Brooks, A. Lockerd, R. A.Peters II, O. C. Jenkins, M. Mataric, M. Bugajska

Abstract

To make the transition from a technological curiosity to productive tools, humanoid robots will require key advances in many areas, including, mechanical design, sensing, embedded avionics, power, and navigation. Using the NASA Johnson Space Center’s Robonaut as a testbed, the DARPA Mobile Autonomous Robot Software (MARS) Humanoids team is investigating technologies that will enable humanoid robots to work effectively with humans and autonomously work with tools. A novel learning approach is being applied that enables the robot to learn both from a remote human teleoperating the robot and an adjacent human giving instruction. When the remote human performs tasks teleoperatively, the robot learns the salient sensory-motor features for executing the task. Once learned, the task may be carried out by fusing the skills required to perform the task, guided by on-board sensing. The adjacent human takes advantage of previously learned skills to sequence the execution of these skills. Preliminary results from initial experiments using a drill to tighten lug nuts on a wheel are discussed.