Abstract:
Advancements in robot capabilities are often achieved through integrating more hardware components. These hardware additions often lead to systems with high power consumption, fragility, and difficulties in control and maintenance. However, is this approach the only path to enhancing robot functionality? In this talk, I introduce the PuzzleBots, a modular multi-robot system with passive mechanisms. Leveraging the inherent agility of individual locomotion, robots can collaborate to assemble into functional structures, reconfigure, and adapt to different environments. I will further present our distributed model predictive control framework, which facilitates precise, real-time control over this highly constrained multi-robot system. By utilizing the environment, coordinating an assembly of multiple robots, and controlling them efficiently, we can improve robot capabilities without complicating the hardware.

Thesis Committee Members:
Katia Sycara, Co-chair
Zeynep Temel, Co-chair
Aaron Johnson
Nikolaus Correll, University of Colorado Boulder

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