Binary Mixtures of Intelligent Active Brownian Particles with Visual Perception
Rajendra Singh Negi, Roland G. Winkler, and Gerhard Gompper

TL;DR
This paper explores the complex collective behaviors of binary mixtures of active Brownian particles with visual perception, revealing diverse nonequilibrium structures and dynamics influenced by steering mechanisms and interaction parameters.
Contribution
It introduces a novel model of active Brownian particles with vision-based, nonreciprocal steering, systematically analyzing emergent structures and behaviors in binary mixtures.
Findings
Formation of multimers, aggregates, and honeycomb lattices.
Predator-prey spatial distribution affected by maneuverability.
Enhanced diffusion at intermediate activity levels.
Abstract
The collective properties of a binary mixture of A- and B-type self-steering particles endowed with visual perception are studied by computer simulations. Active Brownian particles are employed with an additional steering mechanism, which enables them to adjust their propulsion direction relative to the instantaneous positions of neighboring particles, depending on the species, either steering toward or away from them. Steering can be nonreciprocal between the A- and B-type particles. The underlying dynamical and structural properties of the system are governed by the strength and polarity of the maneuverabilities associated with the vision-induced steering. The model predicts the emergence of a large variety of nonequilibrium behaviors, which we systematically characterize for all nine principal sign combinations of AA, BB, AB and BA maneuverabilites. In particular, we observe the…
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Taxonomy
TopicsMicro and Nano Robotics · Pickering emulsions and particle stabilization · Modular Robots and Swarm Intelligence
