Ragesh Kumar Ramachandran

Background

About Ragesh Kumar Ramachandran

A highly motivated individual with a positive outlook, ready to take challenges and explore new areas of the field. I am open for opportunities in solving problems in autonomous driving, multi-robot systems, networked systems and autonomous driving. I’m currently a Planning and Control Engineer at Zoox. Prior to joining Zoox, I was a Post Doctoral Scholar at the University of Southern California in the Robotics Embedded Systems Lab (RESL) under supervision of Prof. Gaurav Sukhatme. Prior to joining USC, I finished my PhD at Arizona State University in the Autonomous Collective System Lab (ACS) under supervision of Dr. Spring Berman. While at ASU, I worked on developing strategies for mapping environmental features of interest – specifically obstacles, collision-free paths, generating a metric map and estimating scalar density fields– in an unknown domain using data obtained by a swarm of resource constrained robots. While at RESL, I’m mostly involved with the development of mathematical models of sub-network failures, e.g, how the failure of one agent leads to a whole sub-network failure, and the design of reliable topologies which mitigates the effects of the failure on the team task performance. Additionally, I had lead the USC's efforts in implementing the developed resilient multi-target tracking strategies using a Unity-based simulator. I have very broad interests in the fields of multi-robot systems, control theory and applied differential geometry. More recently, I have been investigating the application of differential geometry and manifold learning on motion planning. I have evaluated my work on many different platforms such as Crazyfiles, Turtlebot3 Burger and Pheeno. Outside my research I spend time reading, listening and learning topics in Physics, playing Badminton and watching movies.