Sean Kerman

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In this position paper, we synthesize “within the system” models of human influence over bio-inspired swarms, summarizing observations from previous experiments and identifying methods of influence that have not yet been explored. We describe (a) differences among agents that can be controlled by a human and those that can’t, (b) agents that are aware of(More)
This paper uses simulations to identify what types of human influence are afforded by the flocking and swarming structures that emerge from Couzin’s bio-inspired model [4]. The goal is to allow a human to influence a decentralized agent collective without resorting to centralized human control. Evidence is provided that, when nominal agents use(More)
This report formalizes the problem of human-interaction with bio-inspired robot teams (HuBIRT) and then systematically explores properties of various biological collectives that allow human interaction. The goal is to identify models, topologies, and control strategies that allow a decentralized agent collective to be appropriately influenced by a human.(More)
The search for invariants is a fundamental aim of scientific endeavors. These invariants, such as Newton’s laws of motion, allow us to model and predict the behavior of systems across many different problems. In the nascent field of Human-Swarm Interaction (HSI), a systematic identification of fundamental invariants is still lacking. Discovering and(More)
For any crystal structure that can be viewed as a low-symmetry distortion of some higher-symmetry parent structure, one can represent the details of the distorted structure in terms of symmetry-adapted distortion modes of the parent structure rather than the traditional list of atomic xyz coordinates. Because most symmetry modes tend to be inactive, and(More)
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