Patterns and adaptability

Abstract:  The soft matter view to understand collective behavior in natural systems has led to a surge in models to study pattern formation. The functional aspects of these patterns are often understudied and fall under the realm of evolution. In the first part of the talk we will discuss ways by which patterns in natural systems can inspire robotic systems for a particular function and examine a particular instance. We will then look at a possible generalized approach to design robots with robust properties that leverages the classical pattern formation paradigm.

Bio-sketch
Ganga Prasath is currently a post-doc in the School of Engineering and Applied Sciences at Harvard University. He is interested in developing adaptable systems inspired by the natural world. His recent work takes a soft-matter view of robotics and animal behaviour, expanding the pattern formation paradigm with function. He received his PhD from the International Centre for Theoretical Sciences-TIFR for his work on elasticity and hydrodynamics and has a Master’s degree from Ecole Polytechnique. With his background in physics, applied mathematics and engineering, he wants to approach real-world questions with an integrated view of these fields.