Robot design and control

 In order to do interesting robotics one needs interesting robots – in particular robots that have many controllable degrees of freedom along with sufficient sensing capabilities, and are fast and compliant enough so that they can interact with the world the way we do. To meet these requirements, we have designed and built 3-dof modular legs and fingers (ModBots) that can be assembled into various walkers and manipulators. The finger modules shown in the figure are equipped with 3-axis force sensors in the fingertips and potentiometers in the joints, and can move substantially faster than a human finger. We have also acquired some of the most advanced pneumatic robots available (ShadowHand and Kokoro). We found that pneumatic actuators are easy to work with [1], contrary to popular belief. See movies of full body tracking and end effector control on the humanoid robot, and high performance tracking on a simpler pneumatic robot. On the control side, in addition to applying and customizing our latest algorithms, we are excited about the idea of online optimization or model-predictive control. This involves re-optimizing the movement plan at every time step of the real-time control loop, always starting from the current state. See a movie of our robot juggling two balls using online optimization [2]. The above swimming behavior was also generated using a similar approach. A big open question is what happens when the controller is optimized with respect to an innacurate model of the robot. Our results will ball-bouncing indicate that online optimization is surprisingly robust to model errors, but nevertheless a lot more work along these lines is needed.