Engineering Self-Organizing Systems: Theory and Topdown Synthesis Methodology for Resilient Collectives using Kilobot and Molecular Robotics Platforms
Abstract
This project represents a 2-year effort to develop novel techniques for engineering top-down behavior in large collective systems, and to demonstrate their efficacy through experimental validation using two platforms: the Kilobot platform (1000-robot swarm) and a new Molecular Robotics platform which will allow an increase in system scale of many orders of magnitude. The proposed work builds on results from previous seedling grants where we conducted experimental studies on resiliency and top-down synthesis in the Kilobot system. Our efforts involved four Tasks, two each based on the Kilobot and molecular robot systems. The first will develop mathematical prediction models for error cascades we have observed to arise in swarm systems, along with techniques for identifying and suppressing such cascades. The second will compare scalability and resiliency in two distinct approaches to programmable self-assembly, one based on layer-by-layer growth of a target structure, the other based on highly stochastic and parallel removal of robots from a target shape. The third will develop methods for exploration and mapping of nanoscale arenas with molecular robots, and identify unanticipated effects. The fourth will explore molecular-scale fabrication methods through programmable self-assembly using nanorobots. Traditionally, research in swarm robotics has been limited to simulations and small-scale few-robot experiments, due to issues (e.g., cost, operability) associated with large-scale physical systems. However, physical experiments are necessary to validate theory and discover new phenomena, as they reveal unexpected effects illuminating unanticipated considerations. Our overarching goal is to develop both theoretical foundations and validation platforms to support a long-term research agenda for a program in engineering self-organizing systems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 04, 2019
- Source ID
- W911NF1710075
Entities
People
- Radhika Nagpal
Organizations
- Army Contracting Command
- Defense Advanced Research Projects Agency
- Harvard University