I am a first-year Ph.D. student in Computer Science at Arizona State University, advised by Prof. Nakul Gopalan.
I work on learning algorithms that help robots acquire generalizable and reliable skills beyond their training distribution. My long-term goal is to build systems that transfer reusable skills across bodies, tasks, and environments with minimal retraining.
For my Master’s thesis, I developed a behavior cloning method for neural motion planning that works zero-shot across the configuration spaces of multiple manipulators.
I earned my Bachelor’s in Computer Science from
National Institute of Technology, Rourkela.
I’m always looking forward to research collaborations. Feel free to reach out!
🎉 Technical report on AI safety evaluation for AVs accepted at SAE WCX 2024.
Research
Lately I've been thinking about cross-embodiment generalization, long horizon memory for robot policies, and post-training policy improvement methods. Here are recent works that represent my current research direction. Some of my favorites are highlighted.
StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models
Kartikay Milind Pangaonkar*, Prabin Kumar Rath*, Omkar Patil*, Nakul Gopalan International Conference on Intelligent Robots and Systems (IROS), 2026
Training-free approach to improve pretrained VLA policy performance by manipulating the environment's initial state using VLM-based in-context reasoning.
We evaluate performance of state-of-the-art VLA models with StageCraft and show performance improvement across three real world task domains involving diverse distractors and obstructions.
Factorizing Diffusion Policies for Observation Modality Prioritization
Omkar Patil, Prabin Kumar Rath, Kartikay Milind Pangaonkar, Eric Rosen, Nakul Gopalan International Conference on Robotics and Automation (ICRA), 2026 RSS RoboReps Workshop, 2025
Theoretical framework to learn action diffusion models without the need to jointly condition on all input modalities. Our method is robust to deploy against visual distractors, camera occlusions, and appearance changes, maintaining strong performance where standard diffusion policies fail catastrophically.
XMoP: Whole-Body Control Policy for Zero-shot Cross-Embodiment Neural Motion Planning Prabin Kumar Rath, Nakul Gopalan International Conference on Robotics and Automation (ICRA), 2025 RSS Workshop on Embodiment-Aware Robot Learning, 2024
A novel neural policy that solves motion planning problems zero-shot for unseen robotic manipulators. We demonstrate for the first time that configuration-space behavior cloning policies can be learned without embodiment bias and that these learned behaviors can be transferred to novel unseen embodiments in a zero-shot manner.
Evaluating Safety Metrics for Vulnerable Road Users at Urban Traffic Intersections Using High-Density Infrastructure LiDAR System Prabin Kumar Rath, Blake Harrison, Duo Lu, Yezhou Yang, Jeffrey Wishart, Hongbin Yu SAE World Congress Experience, 2024
Real-time VRU safety metrics evaluation strategies for urban traffic intersections.
Validation and Analysis of Driving Safety Assessment Metrics in Real-world Car-Following Scenarios with Aerial Videos
Duo Lu, Sam Haines, Varun Chandra Jammula, Prabin Kumar Rath, Hongbin Yu, Yezhou Yang, Jeffrey Wishart SAE World Congress Experience, 2024
Leader-follower pair identification and metrics evaluation from aerial drone videos.
Design and Performance Analysis of an IoT Based Health Monitoring System for Hospital Management Prabin Kumar Rath, Neelam Mahapatro, Subham Sahoo and Suchismita Chinara IEEE International Conference on Computing Communication and Intelligent Systems, 2021
An IoT health kit for hospitals to assist doctors with medical diagnosis.
Real-time moving object detection and removal from 3D pointcloud data for humanoid navigation in dense GPS‐denied environments Prabin Kumar Rath, Alejandro Ramirez-Serrano, and Dilip Kumar Pratihar Engineering Reports, 2020
Detection and Tracking of Moving Objects (DATMO) algorithm for robot navigation in dynamic environments.
Automation System for Secure Remote Control and Surveillance Prabin Kumar Rath, Neelam Mahapatro and Soumya Nandan Mishra IEEE International Conference on Computer Electrical & Communication Engineering, 2020
Room Automation Module for switching electrical appliances remotely through Web, Bluetooth, and IR.
Autonomous Chess Playing Robot Prabin Kumar Rath, Neelam Mahapatro, Prasanmit Nath and Ratnakar Dash International Conference on Robot & Human Interactive Communication (RO-MAN), 2019
— Listed under top 10 projects in Quest Ingenium 2018
A robot for playing the game of chess physically with an user. Powered with strong chess engines and interactive UI it provides all virtual game features while ensuring the authenticity of the original board game.
Trajectory optimization for the cart pole swing-up problem using Direct collocation, and balancing the inverted pendulum on the cart using LQR control.
Simple LSTM model for classifying colloquial english sentences onto motion commands. Curated text to command dataset for model training using Tensorflow.
4-DOF Cube Stacking Arm Arizona State University, 2023
Customized replica of Turtlebot arm for pick and place tasks. ROS Control and MoveIt stack. Gym compatible environment for training RL agent in Gazebo.
A Bluetooth controlled robot with on board FSR (Force Sensitive Resistor) for weight detection. It has indication LEDs to prompt the user about the detected weights.
