Intelligent Soft Robot Mobility in the Real World

Worcester Polytechnic Institute, Worcester MA

Investigators

Abstract

The goal of this project is the creation of soft, snake-like robots that can navigate through real environments with confined spaces, fragile objects, clutter, rough and/or granular surfaces. The project includes three research thrusts, namely modular mechanical design of a segmented snake robot, low-level algorithms for the robot to execute simple functional motion primitives, and high-level planning algorithms to construct appropriate sequences of motion primitives in order to meet mission objectives. Because they can deform in response to their environment, soft robots can adapt to unexpected circumstances more robustly than a rigid robot. Their high compliance gives soft robots the potential to safely and effectively interact with obstacles, and even to use surrounding objects as aids to locomotion. Robots that embrace touch instead of avoiding it could transform applications through physical human-robot partnership. Specifically, the direct use of assistive and intelligent third-hand devices or soft supernumerary arms could seamlessly provide new capabilities to workers or the disabled. Human-robot collaboration in industry could improve efficiency, reduce cost, and increase the global competitiveness of US manufacturing. The objective of this project is to endow soft robots with intelligence in navigating real-world environments autonomously using a hierarchical control approach from low-level functions and motion primitives to high-level locomotion tasks. The tasks to be accomplished towards this objective include a modular soft robot architecture with distributed actuation, high-density deformation sensing, embedded module-level control, and inter-module communication; control methods to achieve reliable and repeatable dynamic module responses, to optimize performance over time based on past iterations, and to provide high-level decision making by stochastic abstraction and control of the system in its environment through data-driven modeling; and motion planning and locomotion algorithms to find curvature bounded trajectories through cluttered environments, exploit contact to achieve obstacle aided locomotion, and 3-D motion primitives to operate on granular surfaces.