Obstacle Avoidance Using a Monocular Camera. - Kyle Hatch; John Mern; Mykel J. Kochenderfer (CoRR, 2020)

3D Radar Velocity Maps for Uncertain Dynamic Environments. - Ransalu Senanayake; Kyle Beltran Hatch; Jason Zheng; Mykel J. Kochenderfer (IROS, 2021)

Reinforcement Learning for Industrial Control Network Cyber Security Orchestration. - John Mern; Kyle Hatch; Ryan Silva; Jeff Brush; Mykel J. Kochenderfer (CoRR, 2021)

Interpretable Local Tree Surrogate Policies. - John Mern; Sidhart Krishnan; Anil Yildiz; Kyle Hatch; Mykel J. Kochenderfer (SafeAI@AAAI, 2022)

Autonomous Attack Mitigation for Industrial Control Systems. - John Mern; Kyle Hatch; Ryan Silva; Cameron Hickert; Tamim Sookoor; Mykel J. Kochenderfer (DSN Workshops, 2022)

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning. - Rafael Rafailov; Kyle Beltran Hatch; Victor Kolev; John D. Martin; Mariano Phielipp; Chelsea Finn (CoRL, 2023)

Train Offline, Test Online: A Real Robot Learning Benchmark. - Gaoyue Zhou; Victoria Dean; Mohan Kumar Srirama; Aravind Rajeswaran; Jyothish Pari; Kyle Hatch; Aryan Jain; Tianhe Yu; Pieter Abbeel; Lerrel Pinto; Chelsea Finn; Abhinav Gupta 001 (ICRA, 2023)

Contrastive Example-Based Control. - Kyle Beltran Hatch; Benjamin Eysenbach; Rafael Rafailov; Tianhe Yu; Ruslan Salakhutdinov; Sergey Levine; Chelsea Finn (L4DC, 2023)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

Efficient imitation learning with conservative world models. - Victor Kolev; Rafael Rafailov; Kyle Hatch; Jiajun Wu 001; Chelsea Finn (L4DC, 2024)

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. - Rafael Rafailov; Kyle Beltran Hatch; Anikait Singh; Aviral Kumar; Laura M. Smith; Ilya Kostrikov; Philippe Hansen-Estruch; Victor Kolev; Philip J. Ball; Jiajun Wu 001; Sergey Levine; Chelsea Finn (RLJ, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (Robotics: Science and Systems, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (CoRR, 2024)

GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. - Kyle Beltran Hatch; Ashwin Balakrishna; Oier Mees; Suraj Nair 003; Seohong Park; Blake Wulfe; Masha Itkina; Benjamin Eysenbach; Sergey Levine; Thomas Kollar; Benjamin Burchfiel (CoRR, 2024)

A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation. - TRI LBM Team; Jose A. Barreiros; Andrew Beaulieu; Aditya Bhat; Rick Cory; Eric Cousineau; Hongkai Dai; Ching-Hsin Fang; Kunimatsu Hashimoto; Muhammad Zubair Irshad; Masha Itkina; Naveen Kuppuswamy; et al. (CoRR, 2025)