Understanding swarming and collective motion in bacterial populations

One of the hallmarks of a cyber-physical system is the emergence of collective intelligence from the individual elements of the system. For instance, the synthesis of a decision based on multimodal sensory information from the individual nodes of a sensor network. Complex living organisms can also be considered as cyber-physical systems because their survival depends on taking the right decisions based on the collective information gathered from their sensing organs as well as possibly from their neighbours.

In this context, bacteria and similar microbes present an excellent test-bed to study how collective intelligence emerges in a biological system. Given the fact that such systems have evolved over millions of years, the methods they use for decision making and for dealing with noise may be near-optimal and may give us valuable insights in the design of non-living cyber-physical systems.

Autonomous coordinated navigation of drones

The broad objective of the project is to achieve autonomous navigation of multiple drones. There are several important problems that need to be answered before we could achieve this objective. We would like to study these questions in the context of Smart Cities, to enable applications such as delivery of essential supplies like medicines/organs etc. across the city.

Our long-term goals are: (1) Design of drones which can cover city wide areas, (2) suggest infrastructure which could potentially be used in a city for drones, and (3) autonomous navigation strategies for multiple drones.

The goals for the first project year are: (1) Creating an infrastructure for drones, (2) designing of drones, (3) autonomous navigation of a single drone with GPS, and (4) state perception using computer vision for drones.

Development of chemotactic robots

This project focuses on diarrheal diseases, which cause nearly 3,00,000 infant and child mortality in India. So far, animal models have been developed to understand the functioning of the receptor for the bacterial toxin involved in the disease. What has become apparent from these studies is that in vitro models and computational models not only help understand the disease processes and make way for testing new drugs and therapies. There are open questions such as stochasticity in the response of the gut-epithelial cells to bacterial toxins and the effect of peristalsis on the gut-epithelium. These two aspects prompted a bioCPS approach that this project will pursue.