MME Seminar Series: A system design approach for intelligent tensegrity robots

About the event

Presented by Dr. Raman Goyal, TEES Post-Doctoral Researcher, Texas A&M University

Abstract
For centuries researchers have been pushing the boundaries of their respective technical domains, but it is only a few decades ago that research started taking its dig on system design theory. A system design theory encapsulates all individual components design and their simultaneous optimization, i.e., it provides a complete framework to design the structure. This presentation provides a wholesome design approach to integrate structure, control and information architecture to meet some specified performance. The presentation also provides some key results in structure design, dynamic models, and both model-based and learning-based control design of tensegrity systems. The developed system design approach is general and has applications to motion planning and control of a wide variety of applications ranging from autonomous driving to robotic arm manipulation to spacecraft landing/docking.

Biography
Raman Goyal is currently a TEES Postdoctoral Researcher at the Land, Air, and Space Robotics (LASR) Lab in the Department of Aerospace Engineering at Texas A&M University. He completed his Ph.D. from the same program. He obtained his undergraduate degree in Mechanical Engineering from IIT Roorkee, India. He is interested in system design approaches with a focus on integrating structure, signal processing, and control design and has worked on modeling, design, and intelligent learning approaches for control of stochastic nonlinear systems with applications to a wide range of robotic systems.