Date of Award
Doctor of Philosophy (PhD)
Programmable matter is made up of large quantities of particles that can sense, actuate, communicate, and compute. Motivated to imbue these materials with functionality, this thesis presents algorithmic and hardware developments to meet the unique challenges presented by large-scale robot collectives. The quantity of robots involved necessitates algorithms and processes which scale -- in terms of required communication, computation, and memory -- sub-linearly to the number of robots, if scaling at all can not be avoided. Included are methods for communication, movement, synchronization, and localization. To encourage application to a variety of hardware platforms, the theoretical underpinnings of these contributions are made as abstract as possible. These methods are tested experimentally with real hardware, using the Droplet swarm robotics platform I have developed. I also present abstractions which relate global performance properties of a functional object composed of programmable matter to local properties of the hardware platform from which the object is composed. This thesis is further supported by example implementations of functional objects on the Droplets: a TV remote control, a pong game, and a keyboard with mouse.
Klingner, John, "Distributed and Decentralized Algorithms for Functional Programmable Matter" (2018). Computer Science Graduate Theses & Dissertations. 194.