Kartik Paigwar

I am a graduate student at ASU specializing in Robotics and AI. Previously, I was a research associate at Robert Bosch Centre for Cyber-Physical Systems in Indian Institute of Science. I was working with Prof. Shishir Kolathaya and Prof. Shalabh Bhatnagar on learning agile locomotion policies for an open-source low-cost quadruped - Stoch. My research interests revolve around the intersection of robot learning, perception, and navigation.

In a previous life, I was an undergraduate summer research fellow at AIRLab, Politecnico di Milano, Italy advised by Prof. Andrea Bonarini and Dr. Davide Tateo. I worked there on inverse reinforcement learning and dimensionality reduction for a search and rescue robotics task.

I received my bachelor’s degree in Computer Science from Visvesvaraya National Institute of Technology (VNIT), India in September 2019. During my bachelors, I spent most of the time at IvLabs, the robotics laboratory at VNIT supervised by Prof. Shital Chiddarwar. I was also one of the core-coordinators of this lab. I am an avid proponent of student mentorship. I had conducted robotic workshops and mentored many motivated juniors in their projects at Ivlabs. I feel happy to still stay connected and help in their research.

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What's new!

  • December 2020: I joined MS in Robotics and Autonomous Systems program at Arizona State University in Spring '21
  • October 2020: Our paper on "Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach" got accepted in CoRL 2020, MIT, USA.
  • August 2020: Had a wonderful discussion on Sim2Real with Prof. Rupam Mahmood (University of Alberta) and Jessica Hamrick (DeepMind) as a part of 1:1 sessions at CIFAR DLRL Summer School.
  • June 2020: Our paper on "Learning Stable Manoeuvres for Quadruped Robots from Expert Demonstrations" got accepted in RO-MAN 2020, Naples, Italy.
  • June 2020: Accepted to 2020's cohort of Deep Learning Reinforcement Learning Summer School hosted by CIFAR, Mila, Alberta Machine Intelligence Institute (Amii), and Vector Institute. I'm among the 300 applicants selected across the world.

Research

I work on physical robots and in order to teach them to interact with the physical world, work at the intersection of robotics and machine learning..

Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach
Kartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman khetan, Aditya Sagi, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya
4th Conference on Robot Learning (CoRL 2020), MIT, USA
arXiv / project page / github / video / slides

What is the minimum possible control framework that can be deployed to realize stable locomotion behaviors on slopped terrains in medium-size low-cost quadruped robots?

Learning Stable Manoeuvres in Quadruped Robots from Expert Demonstrations
Sashank Tirumala, Sagar Gubbi, Kartik Paigwar, Aditya Sagi, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya
29th International Conference on Robot and Human Interactive Communication
(RO-MAN 2020), Naples, Italy

arXiv / project page / github / video

Generating stable foot trajectories for Omni-directional quadruped motion and learning smooth transitions between these trajectories using expert demonstration.

Gait Library Synthesis for Quadruped Robots via Augmented Random Search
Sashank Tirumala, Aditya Sagi, Kartik Paigwar, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya
arXiv, 2019
arXiv / github: coming soon / video

With a view toward fast deployment of learned locomotion gaits in low-cost hardware, we generate a library of walking trajectories, namely, forward trot, backward trot, side-step, and turn in our custom-built quadruped robot, Stoch 2, using reinforcement learning.

Deep Learning Based Stair Detection and Statistical Image Filtering for Autonomous Stair Climbing
Unmesh Patil, Aniket Gujrathi, Akshay Kulkarni, Aman Jain, Lokeshkumar Malke, Radhika Tekade, Kartik Paigwar, Pradyumn Chaturvedi
3rd IEEE International Conference on Robotic Computing (IRC 2019), Naples, Italy
publication / project page / github / dataset

We present a deep learning based approach for stair detection, statistical filtering on images for the estimation of stair alignment, and novel mechanical design for an autonomous stair climbing robot. The primary objective is to solve the problem of indoor locomotion over staircases

Omnidirectional Visual Navigation System for TurtleBot Using Paraboloid Catadioptric Cameras
Yogesh Phalak, Gaurav Charpe, Kartik Paigwar
International Conference on Robotics and Smart Manufacturing (RoSMa 2018), Chennai, India
publication / video

An omni-directional visual imaging system is constructed using a paraboloid reflector and a monocular camera as a cost effective on-board solution for mobile robot navigation.

Human Gameplay Imitation Through Deep-RL
Kartik Paigwar, Sri Chandra, Purojit Chougule
Bachelor Thesis, Computer Science Department, VNIT, Nagpur
Supervisor : Prof. Meera Dhabu
thesis / dataset / code / video

A Deep RL framework for autonomous skills acquisition in which an agent learns from expert’s gameplays to exhibit a repertoire of skills in an adaptive game environment.

Multi-Expert Inverse Reinforcement Learning
Summer Internship, 2018

Worked on an inverse reinforcement learning problem to find a reward function which could explain the strategies incorporated for robot teleoperation during search and rescue missions.

Multi-Focus Image Fusion with Deep CNNs
Kartik Paigwar, Kartik Patath,
Prujocoject under Prof. Shital Chiddarwar at IvLabs, VNIT
project page

Networks can be trained to fuse mutliple images of a same scene with different focal settings and capture a fully focused image with a minimal specification smart phone camera.

Rubik's Cube Solver
Project under Prof. Shital Chiddarwar at IvLabs, VNIT
project page / github / video /

Rubik's Cube Solver(RCS) is a complete program that can solve any scrambled 3X3X3 cube in less than 22 moves. It uses kociemba algorithm for finding the most optimum solution of a scrambled cube.

Service
Core-Coordinator, 2017 - 2019
Project Mentor, 2016 - 2019
Treasurer, 2018
People

Faculty

Shalabh Bhatnagar (IISc), Ashitava Ghosal (IISc), Bharadwaj Amrutur (IISc), Shishir Kolathaya (IISc), Andrea Bonarini (PoliMi), Shital Chiddarwar (VNIT), Meera Dhabu (VNIT),

Collaborators

Aditya Sagi (IISc), Sasank Tirumala (IIT Madras), Pramod Pal (IISc), Lokesh Krishna (IIT BHU), Naman Khetan (ISM Dhanbad)

Past Mentees

Akshay Kulkarni (VAL Lab), Unmesh Patil (INRIA), Aniket Gujarati (RRC), Akshata Kamath (Manipal)


Yes! You have guessed right. This guy has made a nice webpage.