NRI: Autonomous Synthesis of Haptic Languages

Northwestern University, Evanston IL

Investigators

Abstract

This project develops algorithms that enable a robot to physically explore its environment using touch and to construct a language that it can use to describe that environment. The steps include exploring an environment while actively seeking information and then detecting potential elements of a language to describe what was touched. A secondary phase involves taking the set of language elements and compressing the language itself so that sensing, storage, and communication are all more efficient and more robust. The work will use a robot equipped with a robotic arm, hand, and fingertip sensors to describe objects and surfaces it encounters, all without any information about the objects provided beforehand. The importance of the work stems from the need for robots to operate in environments where touch is the only reliable sensory source. For instance, underwater applications often have limited visibility and dexterous manipulation can suffer from visual occlusion due to the hand itself. This research will enable robots to be more responsive to touch and more reliable in vision-impoverished environments. A key technical tool used in this work is ergodic control, a computational technique that finds exploration strategies matching desired statistics. Symbol detection involves finding definitions of dynamic sensor evolution that minimize measures of variability. Language minimization depends on computing the entropy of a language, and finding the minimal language that has the same level of expressiveness. These three mathematical and algorithmic components need to be used in parallel during language creation, and they each have to respect physical limitations on the part of the robot (e.g., computational limitations and physical limitations). Software will be shared through the Robot Operating System (ROS) and TREP (physical simulation and optimal control software).