Rohan Panicker

I’m a full-stack roboticist with almost 4 years of exposure in Controls, Perception and Embedded Systems. I completed my master's at the University of Washington, Seattle, specializing in Robotics, Controls, and AI.

I was a student researcher at the Robot Learning Lab at the Paul G Allen School, working on developing the autonomy stack for quadrupeds and wheeled robots.

Aside from Robotics, I enjoy singing and playing the guitar (hoping to host shows and start a YouTube channel soon—stay tuned!), and hiking!

Checkout my Bio to know more about my past life!!

Email | CV | Scholar | Github | LinkedIn

Experience

	Amazon Robotics \| Robotics Software Intern Worked on motion and task planning for mobile robots, integrating vision-language models. Built a scalable wrapper for multi-robot systems using AWS. Presented at Amazon Robotics Conference.
	Global Health Labs \| Computer & Machine Learning Intern Developed edge detection and color correction for a COVID test-kit reader. Contributed to embedded design, cutting product cost by over 90%.
	University of Washington, Seattle \| Graduate Student Researcher Developed scalable data collection pipelines for field robots, supporting both wheeled and legged platforms using platform-agnostic Docker containers. Trained reinforcement learning policies in Isaac Sim for quadruped loco-manipulation tasks, including stability, terrain traversal, and object interaction.
	Tata Advanced Systems \| Embedded Software Engineer Implemented object tracking and gimbal control using YOLOv8 and MPC. Improved tracking accuracy via IMU + optical flow fusion.

Projects

Reinforcement Learning for Legged Robots

Out of Distribution Detection for Field Robots

Safe Planning via Receding Hamilton Jacobi Reachability

Poster

DIY Pan Tilt 2DOF setup

Hierarchical Reinforcement Learning for tabular settings

Publications

	Dynamics Models in the Aggressive Off-Road Driving Regime Tyler Han, Sidharth Talia, Rohan Panicker, Preet Shah, Neel Jawale, Byron Boots, Workshop on Resilient Off-Road Autonomy, ICRA, 2024 arXiv
	Sensor fusion between IMU and 2D LiDAR Odometry based on NDT-ICP algorithm for Real-Time Indoor 3D Mapping Rohan Panicker, In this paper, we fuse data from an Inertial Measurement Unit (IMU) and a 2D Light Detection and Ranging (LiDAR) with the help of an Extended Kalman Filter (EKF) for producing a 3D map of an indoor environment. techrXiv
	Voice-controlled upper body exoskeleton Shivam Tripathy, Rohan Panicker, Rohan Panicker, Shubh Shrey, Rutvik Naik, S S Pachpore, This paper is about designing an upper body exoskeleton and utilizing a arduino supported voice recognition module for translating commands into desired actuations. arXiv

News

09/2024 – Joined Amazon Robotics as a Robotics Software Intern
06/2024 – Joined Global Health Labs as a summer intern!
06/2024 – ICRA Workshop paper accepted!
09/2023 – Started Master’s at UW!

	Amazon Robotics \| Robotics Software Intern Worked on motion and task planning for mobile robots, integrating vision-language models. Built a scalable wrapper for multi-robot systems using AWS. Presented at Amazon Robotics Conference.
	Global Health Labs \| Computer & Machine Learning Intern Developed edge detection and color correction for a COVID test-kit reader. Contributed to embedded design, cutting product cost by over 90%.
	University of Washington, Seattle \| Graduate Student Researcher Developed scalable data collection pipelines for field robots, supporting both wheeled and legged platforms using platform-agnostic Docker containers. Trained reinforcement learning policies in Isaac Sim for quadruped loco-manipulation tasks, including stability, terrain traversal, and object interaction.
	Tata Advanced Systems \| Embedded Software Engineer Implemented object tracking and gimbal control using YOLOv8 and MPC. Improved tracking accuracy via IMU + optical flow fusion.