Towards Collective A.I.
Intelligence is a social phenomenon - Maya Mataric, 1993.
The main theme of our lab is investigating Collective Intelligence, and we do it in many ways: robots and theory, bio-inspired and biology. You can read more about the broad themes and projects in our lab on this page, or watch PI Nagpal's IROS Plenary Talk (2022) below. For further details, take a look at our Youtube Channel, Selected Publications, and Lab Highlights.
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 inspection robots, architecture & swarms, soft climbing robots, etc. Our lab is known for several robotic systems: the Kilobot thousand robot swarm, the BlueSwarm underwater robot swarm, the Termes collective construction robots, the Eciton robotica soft self-assembly robots, and the ROOT educational robot (iRobot).
Collective AI: We explore multi-agent AI models, algorithms, and theory inspired by self-organization in biology, e.g. cells, social insects, and fish schools. We investigate biological principles for decentralized coordination, novel communication strategies (e.g. stigmergy, implicit, tactile), and local2global complexity (achieving more than the sum of the parts). Our current algorithmic work is done in close conjunction with experimental robotics or 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 divisions to global tissue networks. Our recent work focused on social insects and "physical" collective intelligence (army ant self-assembly, collective transport in crazy ants, and mound-building termites). We are currently working on fish schools (implicit coordination and hydrodynamics).
Underwater Robot Swarms and Fish Schooling
Self-Assembling Ants and Soft Climbing Robots
Thousand Robot Swarms (Kilobots) and Algorithms:
Termite-inspired Collective Construction
Root Educational Robot
Robobees: Brain, Body, Colony
Programmable Self-Adaptation and Orthotics
Multicellular Topology Networks
Global-to-Local Theory for Pattern Formation
Firefly-inspired Self-Organizing Sensor Networks
Programmable Self-Assembly for Origami-inspired Robots (Amorphous Computing)