Our research addresses the competitive-strategic domain for two opposing teams of agents, which we model in the general framework of a repeated game over network. We are motivated by applications in which, somewhat abstractly, a large collection of autonomous agents must play a game against an adversary or a team of adversaries. We note these applications need not involve explicit adversarial interactions.

Our overall aim in this project is to synthesize desired behaviors in populations of bacterial and mammalian cells. To this goal, we define the basis of a next-generation cyber-physical system (CPS) called biological CPS (bioCPS). The enabling technologies are synthetic biology and micron-scale mobile robotics. Synthetic genetic circuits for decision making and local communication among the cells are automatically synthesized using a Bio-Design Automation (BDA) workflow.

Cyber-physical processors work in harsh environments and often suffer very high operating temperatures.  High temperatures accelerate processor aging and increase failure rate.  Effective thermal-aware management is required to meet the computational demands of the application while reducing processor thermal stress.

The objective of this project is to improve the performance of autonomous systems in dynamic environments by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.

 

Computer systems are increasingly coming to be relied upon to augment or replace human operators in controlling mechanical devices in contexts such as transportation systems, chemical plants, and medical devices, where safety and correctness are critical. A central problem is how to verify that such partially automated or fully autonomous cyber-physical systems (CPS) are worthy of our trust. One promising approach involves synthesis of the computer implementation

A smart and connected community (S&CC) will utilize distributed sensors and embedded computing to seamlessly generate meaningful interpretations that would be of great benefit to individuals, the community, and society, in general. Although rapidly emerging mobile health technology is already tapping into widely used smartphone infrastructure, data collection using smartphone mobile devices is currently limited by the availability of few integrated sensors (e.g., Inertial measurement unit (IMU), camera, optical sensors, temperature sensor, and GPS).

Robotic devices are excellent candidates for delivering repetitive and intensive practice that can restore functional use of the upper limbs, even years after a stroke. Rehabilitation of the wrist and hand in particular are critical for recovery of function, since hands are the primary interface with the world.  However, robotic devices that focus on hand rehabilitation are limited due to excessive cost, complexity, or limited functionality. A design and control strategy for such devices that bridges this gap is critical.

A general model is developed to study how network routing can be reconfigured quickly without incurring transient congestion. Assuming both initial and target configurations are congestion-free, it is known that transient congestion may still occur during the reconfiguration process if links contain a mix of traffic flows following old and new routing rules, resulting from variation of switch reaction time and propagation delay differences among paths. We consider these factors by explicitly incorporating timing uncertainty intervals into the model.