The lessons learned from building 1024 robots w/Michael Rubenstein

What this episode covers

Michael Rubenstein describes how he has taken his robotics research from theory into practice by building cheap and small robots, 1024 of them to be exact. Michael is an assistant professor with a joint appointment in the Electrical Engineering and Computer Science and Mechanical Engineering departments at Northwestern University. His research interest is to advance the control and design of multi-robot systems, enabling their use instead of traditional single robots and to solve problems for which traditional robots are not suitable. Using these multi-robot systems can offer more parallelism, adaptability, and fault tolerance when compared to a traditional single robot. He is also interested in investigating how new technologies will allow for more capable multi-robot systems, and how these technologies impact the design of multi-robot algorithms, especially as these systems begin to number in the hundreds, thousands, or even millions of robots. Michael received his PhD from the University of Southern California in Computer Science. After his PhD, he was a postdoctoral researcher in the Self-Organizing Systems Research Group at Harvard University. He completed his undergraduate degree in Electrical Engineering at Purdue University. Michael first talks to our host Per Sjöborg about his PhD research in algorithms for modular self-reconfigurable robots, at the University of Southern California for Dr. Wei-Min Shen. He then shares his work on the Kilobot project and some of the challenges involved with building 1024 robots and how you can learn different things from actually building the robots than from a simulation. This project helped him fine-tune the algorithms from his earlier research. By working on Kilobot, Michael also learned how to make cheap robots, which fits the educational market well. He talks about this and the robots he has created that can be programmed by school children at robotics summer camps. The Kilobot work was done in the Self-Organizing Systems Research Group at Harvard University. Michael is now faculty at Northwestern University

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