CPS:Medium: Ant-Like Microrobots - Fast, Small, and Under Control
Lead PI:
Nuno Martins
Co-Pi:
Abstract
The objective of this research is to discover new fundamental principles, design methods, and technologies for realizing distributed networks of sub-cm3, ant-sized mobile micro-robots that self-organize into cooperative configurations. The approach is intrinsically interdisciplinary and organized along four main thrusts: (1) Algorithms for distributed coordination and control under severe power, communication, and mobility constraints. (2) Electronics for robot control using event-based communication and computation, ultra-low-power radio, and adaptive analog-digital integrated circuits. (3) Locomotion devices and efficient actuators using rapid-prototyping and MEMS technologies that can operate robustly under real-world conditions. (4) Integration of the algorithms, electronics, and actuators into a fleet of ant-size micro-robots. No robots at the sub-cm3 scale exist because their development faces a number of open challenges. This research will identify and determine means for solving these challenges. In addition, it will provide new solutions to outstanding questions about resource-constrained algorithms, architectures, and actuators that can be widely leveraged in other applications. The PIs will adopt a co-design philosophy that promotes cross-disciplinary research and tight collaboration. Networks of ant-sized robots are expected to be useful in disaster relief, manufacturing, warehouse management, and ecological monitoring, as well as in new unforeseen applications. In addition, the new methods and principles proposed here can be transitioned to other highly-distributed and resource-constrained engineering problems, such as air-traffic control systems. This research program will train Ph.D. students with unique skills in the design of hybrid distributed networks and it will involve undergraduate students, particularly underrepresented minorities and women.
Nuno Martins
Performance Period: 10/01/2009 - 09/30/2014
Institution: University of Maryland College Park
Sponsor: National Science Foundation
Award Number: 0931878