          |
GRASP Seminar Series: Fall 2005
December 9, 11:00 AM, 307 Levine Hall
Daniela Rus
Massachusetts Institute of Technology
“Self-Configuring Robots: Successes and Challenges”
Abstract: We wish to create versatile robots by using self-reconfiguration: hundreds of small modules 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. Self-reconfiguration allows large collections of small robots to 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.
This talk will discuss the challenges and successes of creating self-reconfiguring robots, ranging from designing hardware capable of self-reconfiguration to developing distributed controllers and planners for such systems that are scalable, adaptive, and support real-time behavior.
Biography: Daniela Rus is an associate professor in
the EECS Department at MIT. Previously, she was a professor in the computer
science department at Dartmouth College. She holds a PhD degree in computer
science form Cornell University. Her research interests include distributed
robotics, mobile computing, and self-organization. She was the recipient
of an NSF Career award. She is a Alfred P. Sloan Foundation Fellow and
a class of 2002 MacArthur Fellow.
GRASP
Laboratory
Site maintained by graspadm@grasp.cis.upenn.edu
Last update:
23 August, 2005