The goal of this research is to enable a new era of low-energy mobile robotic Cyber-Physical Systems (CPS). The approach is the simultaneous design of the computing hardware with the computer algorithms, with input from the physics of the system. Applications include, but are not limited to, insect-size robotic bees for artificial pollination, robotic water striders for environmental monitoring, miniature underwater autonomous vehicles for inspection, orally-administered medical robotic vehicles that can intelligently navigate the digestive system, robotic gliders that can operate in the air or underwater for months at a time, and many more. The results will enable low-power computing for artificial intelligence and autonomy to complement the existing low-energy, miniature actuation and sensing systems that have already been developed. This will enable low-energy, miniature mobile robotic CPSs that can still provide provable guarantees on completeness, optimality, robustness and safety.

This project will focus on the development of novel algorithms and novel computing hardware for miniature, energy-efficient mobile robotic CPS. The proposed research will enable low-energy computation for full autonomy by way of minimizing energy consumption during design time and run time, by simultaneously designing the algorithms and the computing hardware. Decision making algorithms will minimize computing energy during run time, for instance, by considering motions that may not require heavy computation for perception and planning. The project will demonstrate the new methods by constructing the smallest fully-autonomous aerial robotic vehicle ever built. We believe the proposed foundational research and the proposed demonstration will kickstart a new cyber-physical systems subfield at the intersection of the mobile robotics literature and the computing hardware (circuits) literature.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1837212
Program Officer
Sandip Roy
Project Start
Project End
Budget Start
2018-10-01
Budget End
2021-09-30
Support Year
Fiscal Year
2018
Total Cost
$1,000,000
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139