Algorithms for Programmable Matter in a Physiological Medium

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In general, programmable matter is any matter that has the ability to change its physical properties (like shape, density, moduli, conductivity, optical properties, etc.) based on user input or autonomous sensing. We are particularly interested in programmable matter composed of nano-robots. Nano-robotics is a rapidly growing interdisciplinary field addressing the assembly and utilization of molecular devices based on nano-scale principles. However, so far there does not exist any particular guideline for designing a nano-robot. Hence now is the ideal time to investigate reasonable models and primitives to rigorously study their algorithmic power. Key applications to nano-robotics are medical target identification, targeted drug delivery, and minimal invasive surgery, to name a few. In all of these medical applications, a swarm of nano-robots acts in the human bloodstream, which is why we are focusing on models and algorithms for nano-robotic swarms in a physiological medium. Besides rigorously designing and evaluating models and efficient algorithms for programmable matter, we will also focus on various extensions such as robustness and hybrid approaches (i.e. programmable matter consisting of active and passive elements).