Robotics

All Publication Topics Autonomous Driving Autonomous Exploration Benchmarks Compression Computer Vision First-Person Video Forecasting Generative Models Imitation Learning Intrinsic Control Machine Learning Manipulation Model-Based Control Offroad Navigation Paper Award Reinforcement Learning Reward Learning Robotics Social Navigation
UBP2 animation
Mohamed Nabail, Leo Kaixuan Cheng*, Jingmin Wang*, Nicholas Rhinehart.
UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning.
arXiv:2606.19328, (arXiv), 2026.
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Reinforcement Learning Machine Learning Model-Based Control Robotics Reward Learning
QPILOTS: Efficient Test-Time Q-Steering for Flow Policies
Yifan Ruan, Chenyang Cao, Andreas Burger, Ali Pesaranghader, Kaveh Kamali, Jaehong Kim, Nandita Vijaykumar, Alan Aspuru-Guzik, Igor Gilitschenski, Nicholas Rhinehart.
QPILOTS: Efficient Test-Time Q-Steering for Flow Policies.
arXiv:2606.14801, (arXiv), 2026.
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Reinforcement Learning Machine Learning Robotics Generative Models
Hshmat Sahak, Aoran Jiao, Nicholas Rhinehart, Tim Barfoot.
OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation.
arXiv:2606.00990, (arXiv), 2026.
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Robotics Model-Based Control Offroad Navigation Machine Learning Forecasting
Tianran Liu, Shengwen Zhao, Mozhgan Pourkeshavarz, Weican Li, Nicholas Rhinehart.
OccSim: Multi-kilometer Simulation with Long-horizon Occupancy World Models.
arXiv:2603.28887, (arXiv), 2026.
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Autonomous Driving Computer Vision Forecasting Generative Models Machine Learning Robotics
Mozhgan Pourkeshavarz, Tianran Liu, Nicholas Rhinehart.
AutoWorld: Scaling Multi-Agent Traffic Simulation with Self-Supervised World Models.
arXiv:2603.28963, (arXiv), 2026.
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Autonomous Driving Computer Vision Forecasting Machine Learning Robotics Generative Models
James R. Han, Mithun Vanniasinghe, Hshmat Sahak, Nicholas Rhinehart, Timothy D. Barfoot.
Ratatouille: Imitation Learning Ingredients for Real-world Social Robot Navigation.
arXiv:2509.17204, (arXiv), 2025.
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Machine Learning Robotics Imitation Learning Social Navigation
Residual Reward Models for Preference-based Reinforcement Learning
Chenyang Cao, Miguel Rogel-García, Mohamed Nabail, Xueqian Wang, Nicholas Rhinehart.
Residual Reward Models for Preference-based Reinforcement Learning.
arXiv:2507.00611, (arXiv), 2025.
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Reward Learning Machine Learning Robotics Reinforcement Learning Manipulation
Foundational LiDAR world model occupancy forecasting result animation
Tianran Liu, Shengwen Zhao, Nicholas Rhinehart.
Towards foundational LiDAR world models with efficient latent flow matching.
Advances in Neural Information Processing Systems, (NeurIPS), 2025.
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Computer Vision Forecasting Machine Learning Robotics Generative Models
James R. Han, Hugues Thomas, Jian Zhang, Nicholas Rhinehart, Timothy D. Barfoot.
DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation.
IEEE Robotics and Automation Letters, (RA-L), 2025.
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Computer Vision Forecasting Machine Learning Model-Based Control Robotics Reinforcement Learning Social Navigation
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting
Jiezhi Yang, Khushi Desai, Charles Packer, Harshil Bhatia, Nicholas Rhinehart, Rowan McAllister, Joseph Gonzalez.
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting.
European Conference on Computer Vision, (ECCV), 2024.
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Autonomous Driving Computer Vision Forecasting Generative Models Machine Learning Robotics
The Waymo Open Sim Agents Challenge
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov.
The Waymo Open Sim Agents Challenge.
Advances in Neural Information Processing Systems, (NeurIPS), 2023.
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Autonomous Driving Benchmarks Computer Vision Forecasting Imitation Learning Machine Learning Robotics
Charles Packer, Nicholas Rhinehart, Rowan McAllister, Matthew a Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E Gonzalez.
Is anyone there? learning a planner contingent on perceptual uncertainty.
Conference on Robot Learning, (CoRL), 2023.
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Autonomous Driving Computer Vision Forecasting Generative Models Machine Learning Model-Based Control Robotics
Dhruv Shah, Arjun Bhorkar, Hrish Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine.
Offline reinforcement learning for visual navigation.
Conference on Robot Learning, (CoRL), 2022.
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Computer Vision Machine Learning Offroad Navigation Reinforcement Learning Robotics
Nitish Dashora, Daniel Shin, Dhruv Shah, Henry Leopold, David Fan, Ali Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine.
Hybrid imitative planning with geometric and predictive costs in off-road environments.
International Conference on Robotics and Automation, (ICRA), 2022.
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Imitation Learning Machine Learning Model-Based Control Offroad Navigation Robotics
ViNG open-world navigation result animation
Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine.
Ving: Learning open-world navigation with visual goals.
IEEE International Conference on Robotics and Automation, (ICRA), 2021.
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Computer Vision Machine Learning Offroad Navigation Model-Based Control Robotics
RECON rapid exploration result animation
Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine.
Rapid exploration for open-world navigation with latent goal models.
Conference on Robot Learning, (CoRL), 2021.
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Autonomous Exploration Offroad Navigation Robotics Model-Based Control
Sequential pointcloud forecasting result animation
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart.
Inverting the pose forecasting pipeline with SPF2: Sequential pointcloud forecasting for sequential pose forecasting.
Conference on robot learning, (CoRL), 2021.
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Autonomous Driving Computer Vision Generative Models Machine Learning Robotics
Nicholas Rhinehart, Jeff He, Charles Packer, Matthew a Wright, Rowan McAllister, Joseph E Gonzalez, Sergey Levine.
Contingencies from observations: Tractable contingency planning with learned behavior models.
IEEE International Conference on Robotics and Automation, (ICRA), 2021.
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Autonomous Driving Computer Vision Forecasting Imitation Learning Machine Learning Model-Based Control Robotics
Parrot robot manipulation result animation
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine.
Parrot: Data-driven behavioral priors for reinforcement learning.
International Conference on Learning Representations, (ICLR), 2020.
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Generative Models Imitation Learning Machine Learning Robotics Manipulation
Arjun Sharma, Mohit Sharma, Nicholas Rhinehart, Kris M Kitani.
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information.
International Conference on Learning Representations (ICLR), (ICLR), 2019.
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Imitation Learning Robotics