Robotic surfaces, whose form and function are under computational control, offer exciting new possibilities for environments that can be customized to fit user-specific needs. When these surfaces can be reprogrammed, a once-static structure can be repurposed to serve multiple different roles over time. In this paper, we introduce such a system. This is an architectural-scale robotic surface, which is able to begin in a neutral state, assume a desired functional shape, and later return to its neutral (flat) position. The surface can then assume a completely different functional shape, all under program control.
Though designed for large-scale applications, our surface uses small, power-efficient constraints to reconfigure itself dynamically. The driving actuation force, instead of being positioned at each "joint" of the structure, is relocated to outer edges of the surface. Within the work presented here, we illustrate the design and implementation of such a surface, showcase a number of human-scale example functional forms that can be achieved (such as dynamic furniture), and present technical evaluations of the results.
Publication
Jesse T. Gonzalez, Juhi Kedia, Sapna Tayal, Sonia Prashant, Alexandra Ion, Scott E. Hudson. 2023. Constraint-Driven Robotic Surfaces, at Human-Scale. In Proceedings of UIST ’23. San Francisco, CA. Oct. 29 – Nov. 1, 2023. DOI: https://dl.acm.org/doi/10.1145/3586183.3606740