This project aims to develop a computational framework and a physical platform for enabling dense networks of micro-robotic swarms for medical applications. The approach relies on a new stochastic framework for design and analysis of dense networks, as well as new fabrication and characterization methods for building and understanding bacteria propelled micro-robotic swarms. This project enhances the CPS science beyond passive networks of millimeter-scale bio-implantable devices with active networks of micro-robotic swarms that could be more effective in combating various critical diseases with minimal impact on the human body.

Three major research objectives are proposed in this project: 1) Statistical physics inspired approach to the modeling and analysis of dense networks of swarms: The theory envisioned for characterizing the dynamics of dense networks of swarms aims at achieving ?beyond Turing? computation via dense networks, designing autonomous reliable communication protocols for dense networks, and estimating and controlling their performance; 2) Fabrication and steering of swarms of bacteria propelled swimming micro-robots: Large numbers of both chemotactic and magnetotactic bacteria integrated micro-robotic bodies will be fabricated using self-assembly and micro/nano-fabrication methods. Chemotaxis and magnetotaxis will be respectively used as passive and active steering mechanisms for navigating the swarms of micro-robots in small spaces to perform specified tasks; 3) Characterization of the behavior and control of bacteria propelled micro-robotic swarms: To validate and fine tune the proposed computational models, the motion and behavior of single and large numbers of bacteria propelled micro-robots will be characterized using optical and other microscopy methods.

Intellectual Merit: The research breakthrough proposed herein consists of building a new physical platform for micro-robotic swarms by using attached bacteria as on-board actuators and chemotaxis and magnetotaxis as passive and active steering control methods, and developing a new computational dense network framework for designing and analyzing such stochastic micro-robotic swarms. The statistical computational framework to be developed in this study will improve understanding of swarming behavior and control of large numbers of bacteria propelled micro-robots. This framework offers an integrated approach towards CPS design that is meant to operate under uncertainty conditions, yet be able to succeed in performing a specified task through self-organization and collective behavior. This bottom-top approach is meant to improve the theoretical foundations of the current computational models of CPS.

Broader Impacts: The resulting computational framework and the physical platform could be adapted to a wide range of different stochastic dense network systems ranging from migration of cancer cell populations or dynamics of virus populations to immune system support and modeling. The proposed swarms of bacteria integrated micro-robots have potential future applications in health-care for the diagnosis of diseases and targeted drug delivery inside the stagnant or low velocity fluids of the human body or the medical diagnosis inside lab-on-a-chip microfluidic devices. Such health-care applications could improve the welfare of our society. To foster learning and training of next generation CPS workforce, the PIs plan to emphasize a cross-disciplinary approach to teaching topics that are usually offered in disjoint tracks. The PIs will integrate the CPS research activities in this study into their newly developed courses, and they will also teach one of these courses jointly. As a joint international educational activity, a three-day Summer School will be held alternately in US and Europe every year on various CPS topics related to our project. This will help building a strong international CPS community and training US and European students in CPS topics. The PIs will present the research results of this project to children, K-12 students, K-12 teachers, IEEE and ACM student members, and college students inside and outside of USA through public lectures. This project and the Sloan Foundation will support underrepresented and minority graduate students in the project. Moreover, underrepresented minority undergraduate students will be trained through the CMU ICES summer outreach program called The SURE Thing and the NSF REU program.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1135850
Program Officer
Ralph Wachter
Project Start
Project End
Budget Start
2011-09-01
Budget End
2016-08-31
Support Year
Fiscal Year
2011
Total Cost
$1,200,000
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213