CAREER: Modeling and Design of Composite Swarming Behaviors

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This project, developing models for complex swarming behaviors by incrementally starting from the properties of an individual agent, which includes noisy sensors and actuators and stochastic behavior, and validating the models by systematic experimentation with physical systems, will bridge the gap between analysis by simple primitives and their composition into complex swarming behaviors. Specifically, this research will consist of a comprehensive study of containment, partitioning, and re-configuration swarming primitives, and then show how they can be composed into complex swarming behaviors such as pattern recognition, sensor-based motion, and adaptive shape change. These primitives and behaviors have been chosen because they challenge existing modeling approaches and lead to independent contributions addressing grand challenge applications by themselves.Inspired by the robust and scalable operation of bees, termites, ants and multi-cellular organisms, the funding of this proposed work will lead to a methodology to compose stochastic swarming behaviors in a principled way using probabilistic models. These models will be grounded in the probabilistic behavior of an individual agent's sensing, actuation, communication and computational properties by modeling the system at multiple levels of abstraction going back and forth from physical experimentation, kinematic models, and stochastic simulations to macroscopic difference equations. By grounding the models in physical experiments, models will be able to serve as design tool for not only the computational, but also the physical properties of an individual agent.Broader Impacts: A principled methodology for modeling and designing swarming systems will create the foundation for designing and deploying swarm robotic systems for search and rescue, environmental response, precision agriculture, and surveillance, among others. At the same time, the ability to design swarms might also shed light on the workings of biological and chemical systems, such as social insects, multi-cellular systems, and self-assembly, enabling the design of complex multi-cellular systems with arbitrary functionality. Finally, algorithms and systems resulting from this research lend themselves to artistic installations, drawing a broad public into the fascination of swarming systems and nurture an understanding for the distributed nature that is common to all living systems. The proposed research will be deeply integrated with education. Specific offerings developed in this integrated research and education plan include: a modular robotic activity that introduces computational thinking to 4th graders, a crash-course on embedded systems geared at 1st year students from under-represented groups, a comprehensive robotics curriculum for upperclassmen, and an interdisciplinary graduate seminar on "Swarm Intelligence" and "Self-Assembly" that will actively involve students from other disciplines and encourage them to apply the proposed multi-level modeling methodology to their research.