In nature, groups of thousands of individuals cooperate to create complex structure purely through local interactions -- cells, ants, bees, fish. How do we create artificial collectives of the scale and complexity that nature achieves? Our group is interested in self-organizing swarms and robotics, where large numbers of relatively simple agents cooperate to produce complex collective behavior. Our work spans Robotics, AI, Biology and has three main themes:

Bio-inspired Robots & Swarms: We develop bio-inspired approaches for building and programming novel robotic systems that rely on large numbers of relatively cheap and simple agents, We are especially interested in the body-brain-colony design space and in embodied intelligence, i.e. how exploiting mechanical intelligence and collective intelligence together can enable novel autonomous robots for new tasks and environments. Topics of interest include: underwater robot swarms, space robotics and architecture/civil applications, climbing and self-assembling robots, soft robotics, swarm/modular robot manufacturing, etc. Our lab is known for several robotic systems: the Kilobot thousand robot swarm, BlueSwarm underwater robots, the Termes collective construction robots, Eciton robotica soft climbing robots, and the Root educational robot. 

Collective Intelligence Algorithms and Theory: We explore multi-agent AI models inspired by self-organization in biology, e.g. cells, social insects, and fish schools. We investigate biological principles for decentralized coordination, scalable/novel communication strategies (stigmergy, implicit, tactile), and complexity (achieving more than the sum of the parts). Our current algorithmic work is done in close conjunction with experimental robot swarms/biology, but in the past we also investigated abstract systems. Our group is especially known for demonstrating global-to-local compilation, i.e. how user-specified global goals can be translated into decentralized local agent interactions with correctness guarantees,

Biological Collectives: We develop mathematical and experiment-driven models of how system-level properties emerge in natural collective systems. We work closely with experimental biologists, and conduct field studies. Our previous work focused on epithelial tissues in fruit fly development, relating local cell programs to global tissue-level outcomes. Our current work focuses on social insects (army ant self-assembly, collective transport and problem-solving in crazy ants, and mound-building termites) and fish schools (implicit coordination and hydrodynamics).