My name is Varun Murali and I am a PhD candidate at MIT working on visual navigation for fast and agile super-vehicles.
I am currently a PhD student at MIT working on agile navigation for drones. Previously, I was a Computer Scientist with the Computer Vision Technology group at SRI International in Princeton, New Jersey, USA working on GPS denied localization algorithms using low cost sensors for various applications. I received my bachelor's degree in Electronics and Communications Engineering from the University of Kent at Canterbury, UK. I have also received master's degrees in Electrical and Computer Engineering and Computer Science with a specialization in computational perception and robotics. I have also held positions at Dynamic Load Monitoring, Southampton, UK and BMW, Munich, Germany. I enjoy research roles and have been involved in different areas of research in robotics and computer vision, including work on semantic localization, active SLAM, guaranteed safe navigation and smooth control for wearable robotics.
Cambridge, MA, USA
Atlanta, GA, USA
Atlanta, GA, USA
Canterbury, UK
Decision Making Under Uncertainty
Most autonomous vehicles, especially high-performance aircraft, must perceive their environment very rapidly using limited computing and sensing resources. In many high-performance applications, slight deviations in the trajectory of the vehicle may enable substantial increase in perception capabilities. Therefore, the trajectory of the vehicle must be chosen carefully to optimize, not only trajectory objectives, but also perception objectives.
Photorealistic Simulation for Robotics
FlightGoggles is envisioned to be development environment that allows the design, implementation, testing and validation of autonomous super-vehicles. FlightGoggles currently provides exteroceptive sensor simulation based on the Unity3D engine as well as vehicle dynamics and inertial sensor simulation capabilities. We aim to train algorithms in this photogrammetric environment and transfer them directly to real world applications.
6D Object Pose Estimation
Pose estimation is critical in many robotics applications, particularly to enable autonomous vehicles to perceive other vehicles around them. We design algorithms that allow 6D pose estimation in challenging scenarios, including heavy occlusion, while under computational constraints.
