Pratik Kunapuli

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I’m a doctoral student in Computer and Information Science (CIS) at GRASP at the University of Pennsylvania. I am co-advised by Vijay Kumar and Dinesh Jayaraman, and am grateful to be supported by the NSF as a GRFP Fellow. My research interests lie at the intersection of machine learning and robotics, specifically related to using reinforcement learning for control of agile and dynamic systems as well as transferring learning approaches from simulation to the real world (sim2real).

Previously, I completed both my BSc and MSc at Georgia Institute of Technology in Electrical and Computer Engineering. During my time there, I worked with Aaron Young in the Exoskeleton Prosthetic Intelligent Controls Lab (EPIC Lab) initially developing controllers for a powered knee and ankle prosthetic and eventually applying machine learning-based state estimation to autonomous hip exoskeletons. My work culminated in my Masters thesis, “Online Adaptation of User State Estimation in a Powered Hip Exoskeleton using Machine Learning”.

Curriculum Vitae

News

Oct 16, 2024 Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems was accepted as a poster to the NeurReps workshop at NeurIPS 2024!
Oct 11, 2024 Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems will be presented at the SymRob workshop at IROS 2024!

Selected Publications

  1. arXiv
    Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems
    Jake Welde*, Nishanth Rao*Pratik Kunapuli*, Dinesh Jayaraman, and Vijay Kumar
    2024
  2. arXiv
    Vision Transformers for End-to-End Vision-Based Quadrotor Obstacle Avoidance
    Anish Bhattacharya, Nishanth Rao, Dhruv Parikh, Pratik Kunapuli, Nikolai Matni, and Vijay Kumar
    2024
  3. IEEE RAL
    Real-Time Gait Phase Estimation for Robotic Hip Exoskeleton Control During Multimodal Locomotion
    Inseung Kang, Dean D. Molinaro, Srijan Duggal, Yanrong Chen, Pratik Kunapuli, and Aaron J. Young
    IEEE Robotics and Automation Letters, 2021
  4. IEEE TMRB
    Real-Time Neural Network-Based Gait Phase Estimation Using a Robotic Hip Exoskeleton
    Inseung Kang*Pratik Kunapuli*, and Aaron J. Young
    IEEE Transactions on Medical Robotics and Bionics, 2020