Tracking-based interactive segmentation of textureless objects. - Karol Hausman; Ferenc Balint-Benczedi; Dejan Pangercic; Zoltan-Csaba Marton; Ryohei Ueda; Kei Okada; Michael Beetz (ICRA, 2013)

Cooperative Control for Target Tracking with Onboard Sensing. - Karol Hausman; Jörg Müller 004; Abishek Hariharan; Nora Ayanian; Gaurav S. Sukhatme (ISER, 2014)

Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor. - Zhe Su; Karol Hausman; Yevgen Chebotar; Artem Molchanov; Gerald E. Loeb; Gaurav S. Sukhatme; Stefan Schaal (Humanoids, 2015)

Active articulation model estimation through interactive perception. - Karol Hausman; Scott Niekum; Sarah Osentoski; Gaurav S. Sukhatme (ICRA, 2015)

Cooperative multi-robot control for target tracking with onboard sensing. - Karol Hausman; Jörg Müller 004; Abishek Hariharan; Nora Ayanian; Gaurav S. Sukhatme (Int. J. Robotics Res., 2015)

Self-calibrating multi-sensor fusion with probabilistic measurement validation for seamless sensor switching on a UAV. - Karol Hausman; Stephan Weiss 002; Roland Brockers; Larry H. Matthies; Gaurav S. Sukhatme (ICRA, 2016)

Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning. - Yevgen Chebotar; Karol Hausman; Zhe Su; Gaurav S. Sukhatme; Stefan Schaal (IROS, 2016)

Occlusion-aware multi-robot 3D tracking. - Karol Hausman; Gregory Kahn; Sachin Patil; Jörg Müller 004; Ken Goldberg; Pieter Abbeel; Gaurav S. Sukhatme (IROS, 2016)

Generalizing Regrasping with Supervised Policy Learning. - Yevgen Chebotar; Karol Hausman; Oliver Kroemer; Gaurav S. Sukhatme; Stefan Schaal (ISER, 2016)

Regrasping Using Tactile Perception and Supervised Policy Learning. - Yevgen Chebotar; Karol Hausman; Oliver Kroemer; Gaurav S. Sukhatme; Stefan Schaal (AAAI Spring Symposia, 2017)

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. - Yevgen Chebotar; Karol Hausman; Marvin Zhang; Gaurav S. Sukhatme; Stefan Schaal; Sergey Levine (ICML, 2017)

Planning high-speed safe trajectories in confidence-rich maps. - Eric Heiden; Karol Hausman; Gaurav S. Sukhatme; Ali-akbar Agha-mohammadi (IROS, 2017)

Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets. - Karol Hausman; Yevgen Chebotar; Stefan Schaal; Gaurav S. Sukhatme; Joseph J. Lim (NIPS, 2017)

Trajectory Optimization for Self-Calibration and Navigation. - James A. Preiss; Karol Hausman; Gaurav S. Sukhatme; Stephan Weiss 002 (Robotics: Science and Systems, 2017)

Observability-Aware Trajectory Optimization for Self-Calibration With Application to UAVs. - Karol Hausman; James A. Preiss; Gaurav S. Sukhatme; Stephan Weiss 002 (IEEE Robotics Autom. Lett., 2017)

Interactive Perception: Leveraging Action in Perception and Perception in Action. - Jeannette Bohg; Karol Hausman; Bharath Sankaran; Oliver Brock; Danica Kragic; Stefan Schaal; Gaurav S. Sukhatme (IEEE Trans. Robotics, 2017)

Learning an Embedding Space for Transferable Robot Skills. - Karol Hausman; Jost Tobias Springenberg; Ziyu Wang 001; Nicolas Heess; Martin A. Riedmiller (ICLR (Poster), 2018)

Scaling Simulation-to-Real Transfer by Learning Composable Robot Skills. - Ryan Julian; Eric Heiden; Zhanpeng He; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (ISER, 2018)

Region Growing Curriculum Generation for Reinforcement Learning. - Artem Molchanov; Karol Hausman; Stan Birchfield; Gaurav S. Sukhatme (CoRR, 2018)

Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations. - Zhanpeng He; Ryan Julian; Eric Heiden; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (CoRR, 2018)

Simultaneous self-calibration and navigation using trajectory optimization. - James A. Preiss; Karol Hausman; Gaurav S. Sukhatme; Stephan Weiss 002 (Int. J. Robotics Res., 2018)

Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. - Abhishek Gupta 004; Vikash Kumar; Corey Lynch; Sergey Levine; Karol Hausman (CoRL, 2019)

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning. - Tianhe Yu; Deirdre Quillen; Zhanpeng He; Ryan Julian; Karol Hausman; Chelsea Finn; Sergey Levine (CoRL, 2019)

Training an Interactive Helper. - Mark Woodward; Chelsea Finn; Karol Hausman (CoRR, 2019)

Confidence-rich grid mapping. - Ali-akbar Agha-mohammadi; Eric Heiden; Karol Hausman; Gaurav S. Sukhatme (Int. J. Robotics Res., 2019)

Learning to Interactively Learn and Assist. - Mark Woodward; Chelsea Finn; Karol Hausman (AAAI, 2020)

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. - Ryan Julian; Benjamin Swanson; Gaurav S. Sukhatme; Sergey Levine; Chelsea Finn; Karol Hausman (CoRL, 2020)

Modeling Long-horizon Tasks as Sequential Interaction Landscapes. - Sören Pirk; Karol Hausman; Alexander Toshev; Mohi Khansari (CoRL, 2020)

Dynamics-Aware Unsupervised Discovery of Skills. - Archit Sharma; Shixiang Gu; Sergey Levine; Vikash Kumar; Karol Hausman (ICLR, 2020)

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. - Ted Xiao; Eric Jang; Dmitry Kalashnikov; Sergey Levine; Julian Ibarz; Karol Hausman; Alexander Herzog (ICLR, 2020)

Gradient Surgery for Multi-Task Learning. - Tianhe Yu; Saurabh Kumar 004; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2020)

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping. - Cristian Bodnar; Adrian Li; Karol Hausman; Peter Pastor; Mrinal Kalakrishnan (Robotics: Science and Systems, 2020)

Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. - Archit Sharma; Michael Ahn; Sergey Levine; Vikash Kumar; Karol Hausman; Shixiang Gu (Robotics: Science and Systems, 2020)

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation. - Ryan Julian; Benjamin Swanson; Gaurav S. Sukhatme; Sergey Levine; Chelsea Finn; Karol Hausman (CoRR, 2020)

A Geometric Perspective on Self-Supervised Policy Adaptation. - Cristian Bodnar; Karol Hausman; Gabriel Dulac-Arnold; Rico Jonschkowski (CoRR, 2020)

Scaling simulation-to-real transfer by learning a latent space of robot skills. - Ryan Julian; Eric Heiden; Zhanpeng He; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (Int. J. Robotics Res., 2020)

Scaling Up Multi-Task Robotic Reinforcement Learning. - Dmitry Kalashnikov; Jake Varley; Yevgen Chebotar; Benjamin Swanson; Rico Jonschkowski; Chelsea Finn; Sergey Levine; Karol Hausman (CoRL, 2021)

AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRL, 2021)

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. - Yevgen Chebotar; Karol Hausman; Yao Lu 006; Ted Xiao; Dmitry Kalashnikov; Jacob Varley; Alex Irpan; Benjamin Eysenbach; Ryan Julian; Chelsea Finn; Sergey Levine (ICML, 2021)

Autonomous Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2021)

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning. - Tianhe Yu; Aviral Kumar; Yevgen Chebotar; Karol Hausman; Sergey Levine; Chelsea Finn (NeurIPS, 2021)

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. - Yevgen Chebotar; Karol Hausman; Yao Lu 006; Ted Xiao; Dmitry Kalashnikov; Jake Varley; Alex Irpan; Benjamin Eysenbach; Ryan Julian; Chelsea Finn; Sergey Levine (CoRR, 2021)

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale. - Dmitry Kalashnikov; Jacob Varley; Yevgen Chebotar; Benjamin Swanson; Rico Jonschkowski; Chelsea Finn; Sergey Levine; Karol Hausman (CoRR, 2021)

Persistent Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (CoRR, 2021)

AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRR, 2021)

A Metric Space Perspective on Self-Supervised Policy Adaptation. - Cristian Bodnar; Karol Hausman; Gabriel Dulac-Arnold; Rico Jonschkowski (IEEE Robotics Autom. Lett., 2021)

Offline Reinforcement Learning at Multiple Frequencies. - Kaylee Burns; Tianhe Yu; Chelsea Finn; Karol Hausman (CoRL, 2022)

Inner Monologue: Embodied Reasoning through Planning with Language Models. - Wenlong Huang; Fei Xia 002; Ted Xiao; Harris Chan; Jacky Liang; Pete Florence; Andy Zeng 001; Jonathan Tompson; Igor Mordatch; Yevgen Chebotar; Pierre Sermanet; Tomas Jackson; et al. (CoRL, 2022)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Brian Ichter; Anthony Brohan; Yevgen Chebotar; Chelsea Finn; Karol Hausman; Alexander Herzog; Daniel Ho; Julian Ibarz; Alex Irpan; Eric Jang; Ryan Julian; Dmitry Kalashnikov; et al. (CoRL, 2022)

Autonomous Reinforcement Learning: Formalism and Benchmarking. - Archit Sharma; Kelvin Xu; Nikhil Sardana; Abhishek Gupta 004; Karol Hausman; Sergey Levine; Chelsea Finn (ICLR, 2022)

How to Leverage Unlabeled Data in Offline Reinforcement Learning. - Tianhe Yu; Aviral Kumar; Yevgen Chebotar; Karol Hausman; Chelsea Finn; Sergey Levine (ICML, 2022)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Michael Ahn; Anthony Brohan; Noah Brown; Yevgen Chebotar; Omar Cortes; Byron David; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Daniel Ho; Jasmine Hsu; et al. (CoRR, 2022)

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. - Yevgen Chebotar; Quan Vuong; Karol Hausman; Fei Xia 002; Yao Lu 006; Alex Irpan; Aviral Kumar; Tianhe Yu; Alexander Herzog; Karl Pertsch; Keerthana Gopalakrishnan; Julian Ibarz; et al. (CoRL, 2023)

Open-World Object Manipulation using Pre-Trained Vision-Language Models. - Austin Stone; Ted Xiao; Yao Lu 006; Keerthana Gopalakrishnan; Kuang-Huei Lee; Quan Vuong; Paul Wohlhart; Sean Kirmani; Brianna Zitkovich; Fei Xia 002; Chelsea Finn; Karol Hausman (CoRL, 2023)

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. - Brianna Zitkovich; Tianhe Yu; Sichun Xu; Peng Xu 010; Ted Xiao; Fei Xia 002; Jialin Wu; Paul Wohlhart; Stefan Welker; Ayzaan Wahid; Quan Vuong; Vincent Vanhoucke; et al. (CoRL, 2023)

PaLM-E: An Embodied Multimodal Language Model. - Danny Driess; Fei Xia 002; Mehdi S. M. Sajjadi; Corey Lynch; Aakanksha Chowdhery; Brian Ichter; Ayzaan Wahid; Jonathan Tompson; Quan Vuong; Tianhe Yu; Wenlong Huang; Yevgen Chebotar; et al. (ICML, 2023)

Jump-Start Reinforcement Learning. - Ikechukwu Uchendu; Ted Xiao; Yao Lu 006; Banghua Zhu; Mengyuan Yan; Joséphine Simon; Matthew Bennice; Chuyuan Fu; Cong Ma 001; Jiantao Jiao; Sergey Levine; Karol Hausman (ICML, 2023)

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. - Abhishek Gupta 004; Corey Lynch; Brandon Kinman; Garrett Peake; Sergey Levine; Karol Hausman (ICRA, 2023)

Code as Policies: Language Model Programs for Embodied Control. - Jacky Liang; Wenlong Huang; Fei Xia 002; Peng Xu 010; Karol Hausman; Brian Ichter; Pete Florence; Andy Zeng 001 (ICRA, 2023)

Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents. - Wenlong Huang; Fei Xia 002; Dhruv Shah; Danny Driess; Andy Zeng 001; Yao Lu 006; Pete Florence; Igor Mordatch; Sergey Levine; Karol Hausman; Brian Ichter (NeurIPS, 2023)

RT-1: Robotics Transformer for Real-World Control at Scale. - Anthony Brohan; Noah Brown; Justice Carbajal; Yevgen Chebotar; Joseph Dabis; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Jasmine Hsu; Julian Ibarz; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (Robotics: Science and Systems, 2023)

Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models. - Ted Xiao; Harris Chan; Pierre Sermanet; Ayzaan Wahid; Anthony Brohan; Karol Hausman; Sergey Levine; Jonathan Tompson (Robotics: Science and Systems, 2023)

Scaling Robot Learning with Semantically Imagined Experience. - Tianhe Yu; Ted Xiao; Jonathan Tompson; Austin Stone; Su Wang; Anthony Brohan; Jaspiar Singh; Clayton Tan; Dee M; Jodilyn Peralta; Karol Hausman; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control. - Wenlong Huang; Fei Xia 002; Dhruv Shah; Danny Driess; Andy Zeng 001; Yao Lu 006; Pete Florence; Igor Mordatch; Sergey Levine; Karol Hausman; Brian Ichter (CoRR, 2023)

Open-World Object Manipulation using Pre-trained Vision-Language Models. - Austin Stone; Ted Xiao; Yao Lu 006; Keerthana Gopalakrishnan; Kuang-Huei Lee; Quan Vuong; Paul Wohlhart; Brianna Zitkovich; Fei Xia 002; Chelsea Finn; Karol Hausman (CoRR, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (CoRR, 2023)

Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities. - Markus Wulfmeier; Arunkumar Byravan; Sarah Bechtle; Karol Hausman; Nicolas Heess (CoRR, 2023)

What Makes Pre-Trained Visual Representations Successful for Robust Manipulation? - Kaylee Burns; Zach Witzel; Jubayer Ibn Hamid; Tianhe Yu; Chelsea Finn; Karol Hausman (CoRL, 2024)

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches. - Priya Sundaresan; Quan Vuong; Jiayuan Gu; Peng Xu 010; Ted Xiao; Sean Kirmani; Tianhe Yu; Michael Stark 003; Ajinkya Jain; Karol Hausman; Dorsa Sadigh; Jeannette Bohg; et al. (CoRL, 2024)

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches. - Jiayuan Gu; Sean Kirmani; Paul Wohlhart; Yao Lu 006; Montserrat Gonzalez Arenas; Kanishka Rao; Wenhao Yu 003; Chuyuan Fu; Keerthana Gopalakrishnan; Zhuo Xu; Priya Sundaresan; Peng Xu 010; et al. (ICLR, 2024)

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. - Chengshu Li 002; Jacky Liang; Andy Zeng 001; Xinyun Chen; Karol Hausman; Dorsa Sadigh; Sergey Levine; Li Fei-Fei 001; Fei Xia 002; Brian Ichter (ICML, 2024)

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. - Soroush Nasiriany; Fei Xia 002; Wenhao Yu 003; Ted Xiao; Jacky Liang; Ishita Dasgupta 001; Annie Xie; Danny Driess; Ayzaan Wahid; Zhuo Xu; Quan Vuong; Tingnan Zhang; et al. (ICML, 2024)

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. - Isabel Leal; Krzysztof Choromanski; Deepali Jain; Avinava Dubey; Jake Varley; Michael S. Ryoo; Yao Lu 006; Frederick Liu; Vikas Sindhwani; Quan Vuong; Tamás Sarlós; Ken Oslund; et al. (ICRA, 2024)

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)

RoboVQA: Multimodal Long-Horizon Reasoning for Robotics. - Pierre Sermanet; Tianli Ding; Jeffrey Zhao; Fei Xia 002; Debidatta Dwibedi; Keerthana Gopalakrishnan; Christine Chan; Gabriel Dulac-Arnold; Sharath Maddineni; Nikhil J. Joshi; Pete Florence; Wei Han 002; et al. (ICRA, 2024)

GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks. - Kaylee Burns; Ajinkya Jain; Keegan Go; Fei Xia 002; Michael Stark 003; Stefan Schaal; Karol Hausman (IROS, 2024)

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. - Michael Ahn; Debidatta Dwibedi; Chelsea Finn; Montse Gonzalez Arenas; Keerthana Gopalakrishnan; Karol Hausman; Brian Ichter; Alex Irpan; Nikhil J. Joshi; Ryan Julian; Sean Kirmani; Isabel Leal; et al. (CoRR, 2024)

π0: A Vision-Language-Action Flow Model for General Robot Control. - Kevin Black; Noah Brown; Danny Driess; Adnan Esmail; Michael Equi; Chelsea Finn; Niccolo Fusai; Lachy Groom; Karol Hausman; Brian Ichter; Szymon Jakubczak; Tim Jones; et al. (CoRR, 2024)

Foundation models in robotics: Applications, challenges, and the future. - Roya Firoozi; John Tucker 001; Stephen Tian; Anirudha Majumdar; Jiankai Sun; Weiyu Liu; Yuke Zhu; Shuran Song; Ashish Kapoor; Karol Hausman; Brian Ichter; Danny Driess; et al. (Int. J. Robotics Res., 2025)

π0.5: a Vision-Language-Action Model with Open-World Generalization. - Physical Intelligence; Kevin Black; Noah Brown; James Darpinian; Karan Dhabalia; Danny Driess; Adnan Esmail; Michael Equi; Chelsea Finn; Niccolo Fusai; Manuel Y. Galliker; Dibya Ghosh; et al. (CoRR, 2025)