Challenges and Successes in Self-reconfiguring Robots

by Daniela Rus

Department of Computer Science, Dartmouth, and
Department of EECS, MIT

Abstract

Our goal is to create versatile robots by using self-reconfiguration: hundreds of small modules will autonomously organize and reorganize as geometric structures to best fit the terrain on which the robot has to move, the shape of the object the robot has to manipulate, or the sensing needs for the given task. Large collections of small robots will actively organize as the most optimal geometric structure to perform useful coordinated work.

A self-reconfiguring robot consists of a set of identical modules that can dynamically and autonomously reconfigure in a variety of shapes, to best fit the terrain, environment, and task. Self-reconfiguration leads to versatile robots that can support multiple modalities of locomotion and manipulation. Self-reconfiguring robots constitute large scale distributed systems. Because the modules change their location continuously they also constitute ad-hoc networks.

In this talk I will describe two self-reconfiguring robots we designed and built: the Crystal robot and the Molecule Robot. I will also talk about algorithmic challenges related to controlling large scale self-reconfiguring robots, focusing on one hardware-specific distributed planner and on another more generic distributed planner and its instantiations to specific robot architectures. Finally, I will discuss some systems issues that arise in building a communication infrastructure for such robots.


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