Our Research

Biological systems, from multicellular organisms to social insects ("superorganisms"), get tremendous mileage from the cooperation of vast numbers of cheap, unreliable, and limited individuals. As we build artificial systems with similar characteristics --- robot swarms, modular robots, sensor networks, programmable materials --- can we achieve the kind of complexity and reliability that nature achieves?

Our group is interested in self-organizing multi-agent systems, where large numbers of simple agents cooperate to produce complex and robust global behavior. We study bio-inspired paradigms for designing and programming collective intelligence in robotics and networks, drawing inspiration mainly from multicellular biology and social insects. We also investigate models of self-organization in biology, specifically how cells and insects cooperate to achieve complex tasks.

A common theme in all of our work is understanding the relationship between local and global behavior: how does robust collective behavior arise from many locally interacting agents, and how can we program the local interations of simple agents to achieve the global behaviors we want.

School of Engineering and Applied Sciences
Wyss Institute for Biologically Inspired Engineering
Harvard University

  cells ants bees fish 1 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 hello world 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 agents robots networks

Research Areas

We work on three main areas:

  • Bio-inspired Multi-agent Models and Theory

    We explore artificial multi-agent models inspired by self-organising and self-repairing behavior in biology. We are especially interested in global-to-local compilation and theory, i.e. how user-specified global goals can be translated into local agent interactions and how one can reason about the correctness and complexity of agent rules. Our goal is to show how biological design principles can be formally captured, generalized to new tasks, and theoretically analyzed.

  • Bio-inspired Multi-agent Robotic Systems

    We study bio-inspired approaches for designing and programming robotic systems that rely on large numbers of relatively cheap and simple agents, e.g. reconfigurable modular robots, robot swarms (TERMES, Kilobots, Robobees) and sensor networks. We are especially interested in the design and analysis of algorithms for decentralized coordination, global-to-local programming, and the physical design of autonomous robot collectives.

  • Biological Multi-agent Systems

    We develop mathematical and computational models of individual behavior to investigate how system-level properties emerge in collective systems. We work closely with experimental biologists. Most of our current work is focused on epithelial tissues and fruit fly development; our goal is to elucidate the relationship between local cell programs and global tissue-level outcomes during development and disease. Our recent work focusses on how termites coordinate to assemble complex nest structures.

Our lab is part of the Computer Science Area, within the School of Engineering and Applied Sciences at Harvard. We are part of the Artificial Intelligence research group (AIRG) and the SEAS Robotics Group. Our lab is a core member of the Wyss Institute for Biologically Inspired Engineering at Harvard, where we co-lead the Bio-inspired Robotics Platform. We are also affiliated with the Systems Biology PhD program at Harvard. We are located on the 2nd floor of the Maxwell-Dworkin Building, at 33 Oxford Street, Cambridge.


SELECTED RECENT PUBLICATIONS

Designing Collective Behavior in a Termite-Inspired Robot Construction Team
Justin Werfel, Kirstin Petersen, Radhika Nagpal
Science, Vol 343, no 6172, 14 Feb 2014 (link)

Autonomous MAV guidance with a lightweight omnidirectional vision sensor
Richard Moore, Karthik Dantu, Geoffery Barrows, Radhika Nagpal
IEEE Intl. Conf on Robotics and Automation (ICRA), June 2014. (pdf)

Robotic Construction of Arbitrary Shapes with Amorphous Materials
Nils Napp, Radhika Nagpal
IEEE Intl. Conf on Robotics and Automation (ICRA), June 2014. (pdf)

A computational framework for identifying design guidelines to increase the penetration of targeted nanoparticles into tumors
Sabine Hauert, Spring Berman, Radhika Nagpal, Sangeeta N. Bhatia
Nano Today, Dec 2013. (link)

Massive Uniform Manipulation: Controlling Large Populations of Simple Robots With a Common Input Signal
Becker, Habibi, Werfel, Rubenstein, McLurkin
IEEE Intl. Conf. on Intelligent Robots and Systems (IROS), Nov 2013. (pdf)


USEFUL LINKS

Youtube Channel: See Videos of our work
Kilobots: Buy from K-Team Corp or Make Your Own
Join us: Here's information on applying to our group


RECENT NEWS


AFRON Contest, Mar 2014
Mike Rubenstein's Aerobot won first and second places in three categories: hardware, software, and curriculum, in the AFRON "Ultra Affordable Educational Robot Project" design challenge. Aerobot was designed to cost only $10, be easily manufactured, and can be programmed with the graphical language minibloq.

Also, Aerobot will be featured for the first time this year in a STEM summer camp, i2camp BugBots, aimed at 5th-7th graders. Every kid gets to take their robot home.

Science, Feb 2014
Our paper on the termite-inspired collective construction robots is in this month's issue of Science magazine, along with a perspective by Prof. Korb. Some news articles on our work (Boston Globe, NPR, Nature News).

See a Movie of our work

Radcliffe Video, Dec 2013
Radhika and other members of the lab are featured in Exploring Collective Intelligence, a video by the Radcliffe Institute.



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