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Rohan ThakkerI am a full-stack Roboticist. My research focus is on developing "tightly coupled" planning, control and vision algorithms to build resilient autonomy capabilies and deploy them on real-world missions. I have been working at NASA's Jet Propulsion Laboratory as a Robotics Research Technologist since 2017, prior to which, I got my graduate degree in Robotics at Carnegie Mellon Unversity, Pittsburgh, USA and undergrad in Mechanical Engineering at Visvesvaraya National Institute of Technology, Nagpur, India.
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Experience
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Autonomy Lead EELS, Snake Robot to Explore Enceladus Sep 2022 – Present Leading the Autonomy team of over 15 JPL researchers and engineers to develop risk-aware decision-making capabilities to achieve resilient mobility in perceptually degraded extreme environments. Papers: <stay tuned> |
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Learning for Planning Team Lead
High-speed Autonomous Off-road Navigation DARPA RACER (Ex-1) In collaboration with UC Berkely, MIT, and GaTech Oct 2021 – Sep 2022 Led the collaboration with UC Berkeley and MIT to developed classical, imitation learning and reinforcement learning-based motion planning algorithms and deployed on full-scale off-road vehicles in Mojave Dessert. Papers: [1], <stay tuned> |
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Guidance, Navigation and Controls Lead DARPA Subterranean Challenge (Tunnel Circuit) In collaboration with Caltech, MIT, Boston Dynamics, and more! June 2018 – Feb 2020 Led the GNC group of Team Costar to develop the full autonomous mobility stack for drones, legged robots, and wheeled robots deployed in real-worled environments such as the tunnels, mines, and caves. Finished 2nd in Tunnel Circuit and 1st in Urban Circuit. Papers: [1], [2], [3], [4], [5], [6], [7], [8] |
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Autonomy Researcher Verifiable Mulit-agent Autonomy for Mars Helicopter and Rover In collaboration with Prof. Richard Murray & Prof. Aaron Ames, Caltech May 2017 – May 2018 Developed a framework for multi-agent risk-aware planning under uncertainty for coordination of Mars Rover and Mars Helicopter to generate policies that maximize the probability of satisfaction of a mission specification defined by Linear Temporal Logic (LTL) using POMDPs. Papers: [1], [2], [3], [4], [5] |
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Guidance, Navigation and Controls Developer GPS-deined High-speed Autonomous Quadrotor Flight In collaboration with Google Tango Team, ARL Mar 2017 – Feb 2018 Developed planning and controls algorithms and software by exploiting geometric controllers and differential flatneess. Drone achieved speeds over 10m/s in indoor GPS-denied environments! Papers: [1], [2], [3], [4] |
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Graduate Student Researcher, CMU
Kinodynamic Motion Planning for Dual Arm Manipulation & Non-linear control of quadrotors Co-adivsed by Dr. Siddhartha Srinivasa and Dr. Koushil Sreenath Developed a sampling-based Asymptotically Optimal Kinodynamic Motion Planner for high dimensional non-euclidean spaces. Demonstrated an order of magnitude improvement in convergence rate compared to state-of-the-art Hierarchical Rejection Sampling Algorithms. Paper(s): [1] Picture credits (1), (2) |