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In my past life, I was a student collaborator working with Nidhi Seethapathi at the Seethapathi Motor Control Lab, MIT on the development of a framework to study human locomotor adaptation. Prior to that, I was a guest researcher at the Movement Generation and Control Group, Max Planck Institute for Intelligent Systems, working on control strategies for agile and dynamic bipedal locomotion under the supervision of Majid Khadiv. I was also a student researcher at the Stochastic Robotics Lab, Indian Institute of Science, jointly advised by Shishir Kolathaya and Ayonga Hereid, where I worked towards the development of a lightweight control frameworks for robust proprioceptive bipedal walking. Apart from my research activities, I also co-founded and led the student research group, RoboReG at IIT BHU. As the technical lead of this group, I have successfully mentored several student-driven research projects and teams in events/competitions of national significance.
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My research focuses on extending the athletic intelligence in robots, thereby leveraging their motor skills to be on par with that found in the animal kingdom: the result of centuries of evolution. Though nature stands as an unparalleled motivation for us to mimic through machines, I realize its cruel mockery and envy its athletic supremacy every time I see the energy-exploding gallop of a cheetah or the agile flight maneuver of a soaring eagle or the sudden sprint by a raging ostrich. Decades of development in robot actuation, sensing, and computation have finally paved the way for such machines to be a reality. However, the algorithmic principles to attain such extreme performance in robots while solving diverse tasks continues to be the final piece of the puzzle, calling to develop techniques that show strong empirical results backed by unassailable mathematical proofs and an understanding through first principles. To this end, I am interested in adopting formal methods from reinforcement learning and optimization to realize extreme performance in hybrid underactuated robotic systems with an optimal balance of performance, reliability, and guarantees. |
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Lokesh Krishna, Quan Nguyen Accepted at IROS 2023 arXiv / video |
 
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Lokesh Krishna*, Guillermo Castillo*, Utkarsh Mishra, Ayonga Hereid, Shishir Kolathaya Accepted at IEEE RA-L (journal) and ICRA 2022 IEEE Xplore / arXiv / video |
 
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Lokesh Krishna, Utkarsh Mishra, Guillermo Castillo, Ayonga Hereid, Shishir Kolathaya Accepted at IROS 2021 IEEE Xplore / arXiv / project page / video |
 
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Kartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman khetan, Aditya Sagi, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya Accepted at CoRL 2020 PMLR / arXiv / project page / GitHub / video / slides |
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Lokesh Krishna, Inseung Kang, Nidhi Seethapathi |
 
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Multi Stage Learning Lokesh Krishna , Miroslav Bogdanovic , Majid Khadiv , Ludovic Righetti GitHub (request acess) / video |
 
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Lokesh Krishna, Prityush Chandra, Prajwal Nair, MK Meshram GitHub / preprint |
 
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Yash Sahijwani, Raghav Soni, Ayush Kumar Shaw, Niranth Sai, Lokesh Krishna National Finalists, Flipkart Grid 2.0 Robotics Challenge Slides / GitHub / video |
 
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Lokesh Krishna, Nishant Kumar, Niranth Sai GitHub / video |
 
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Lokesh Krishna, Shishir Kolathaya GitHub |
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MiniCheetahEnv: A modular pybullet environment for mini-cheetah with an MPC controller
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ArduinoMLP: A NN netowrk library for Arduino
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RaisimStoch2: a simulation environment for Stoch2 in RAISIM
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GestureBot: A mobile manpualtion platform for gesture controlled teleoperation
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GAMCA: Genetic Algorithm to solve Maze like Cellular Automata
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Technical Head, 2020-21
Founder, 2020 |
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Coordinator, Robotics Summer Camp 2021
Mentor, Robotics Summer Camp 2020 Panel Member, 2020-21 Mentor, 2019-20 |
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I am a Roboticist, I dont make cool websites. He does. |