Karol Hausman

Hi there! I'm a co-founder of Physical Intelligence (Pi) where we aim to bring AI into the physical world. Before starting Pi, I was a Staff Research Scientist at Google Deepmind and an Adjunct Professor at Stanford. I'm interested in enabling robots to acquire general-purpose skills in the real world. I also co-taught a class at Stanford on Deep Reinforcement Learning (CS 224R).



News

Research


I split my research into three buckets: deep robotic learning, interactive and active perception but these days, I focus entirely on the first one. Lately I've been particularly excited about building and using foundation models for decision making. My research has been covered by a number of news outlets including: The New York Times (front page!), The Washington Post, 60 minutes, Techcrunch, WiRED, Quanta Magazine, CNET, The Verge and others. You can find all my work on my Google Scholar:



(Deep) Robotic Learning

In my research on deep robotic learning, I focus on how we can apply modern deep learning techniques to various robotic applications.

Open X-Embodiment: Robotic Learning Datasets and RT-X Models
under submission, 2023
A. Padalkar, A. Pooley, A. Jain, A. Bewley, A. Herzog, A. Irpan, A. Khazatsky, A. Rai, A. Singh, A. Brohan, A. Raffin, A. Wahid, B. Burgess-Limerick, B. Kim, B. Schölkopf, B. Ichter, C. Lu, C. Xu, C. Finn, C. Xu, C. Chi, C. Huang, C. Chan, C. Pan, C. Fu, C. Devin, D. Driess, D. Pathak, D. Shah, D. Büchler, D. Kalashnikov, D. Sadigh, E. Johns, F. Ceola, F. Xia, F. Stulp, G. Zhou, G. S. Sukhatme, G. Salhotra, G. Yan, G. Schiavi, G. Kahn, H. Su, H. Fang, H. Shi, H. Ben Amor, H. I Christensen, H. Furuta, H. Walke, H. Fang, I. Mordatch, I. Radosavovic, I. Leal, J. Liang, J. Abou-Chakra, J. Kim, J. Peters, J. Schneider, J. Hsu, J. Bohg, J. Bingham, J. Wu, J. Wu, J. Luo, J. Gu, J. Tan, J. Oh, J. Malik, J. Tompson, J. Yang, J. J. Lim, J. Silvério, J. Han, K. Rao, K. Pertsch, K. Hausman, K. Go, K. Gopalakrishnan, K. Goldberg, K. Byrne, K. Oslund, K. Kawaharazuka, K. Zhang, K. Rana, K. Srinivasan, L. Y. Chen, L. Pinto, L. Tan, L. Ott, L. Lee, M. Tomizuka, M. Du, M. Ahn, M. Zhang, M. Ding, M. K. Srirama, M. Sharma, M. J. Kim, N. Kanazawa, N. Hansen, N. Heess, N. J. Joshi, N. Suenderhauf, N. Di Palo, N. M. M. Shafiullah, O. Mees, O. Kroemer, P. R. Sanketi, P. Wohlhart, P. Xu, P. Sermanet, P. Sundaresan, Q. Vuong, R. Rafailov, R. Tian, R. Doshi, R. Martín-Martín, R. Mendonca, R. Shah, R. Hoque, R. Julian, S. Bustamante, S. Kirmani, S. Levine, S. Moore, S. Bahl, S. Dass, S. Sonawani, S. Song, S. Xu, S. Haldar, S. Adebola, S. Guist, S. Nasiriany, S. Schaal, S. Welker, S. Tian, S. Dasari, S. Belkhale, T. Osa, T. Harada, T. Matsushima, T. Xiao, T. Yu, T. Ding, T. Davchev, T. Z. Zhao, T. Armstrong, T. Darrell, V. Jain, V. Vanhoucke, W. Zhan, W. Zhou, W. Burgard, X. Chen, X. Wang, X. Zhu, X. Li, Y. Lu, Y. Chebotar, Y. Zhou, Y. Zhu, Y. Xu, Y. Wang, Y. Bisk, Y. Cho, Y. Lee, Y. Cui, Y. Wu, Y. Tang, Y. Zhu, Y. Li, Y. Iwasawa, Y. Matsuo, Z. Xu, Z. J. Cui.
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
under submission, 2023
K. Burns, Z. Witzel, J. Ibn Hamid, T. Yu, C. Finn, K. Hausman
RoboVQA: Multimodal Long-Horizon Reasoning for Robotics
under submission, 2023
P. Sermanet, T. Ding, J. Zhao, F. Xia, D. Dwibedi, K. Gopalakrishnan, C. Chan, G. Dulac-Arnold, S. Maddineni, N. J. Joshi, P. Florence, W. Han, R. Baruch, Y. Lu, S. Mirchandani, P. Xu, P. Sanketi, K. Hausman, I. Shafran, B. Ichter, Y. Cao
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
under submission, 2023
J. Gu, S. Kirmani, P. Wohlhart, Y. Lu, M. Gonzalez Arenas, K. Rao, W. Yu, C. Fu, K. Gopalakrishnan, Z. Xu, P. Sundaresan, P. Xu, H. Su, K. Hausman, C. Finn, Q. Vuong, T. Xiao
RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches
under submission, 2023
P. Sundaresan, Q. Vuong, J. Gu, P. Xu, T. Xiao, S. Kirmani, T. Yu, M. Stark, A. Jain, K. Hausman, D. Sadigh, J. Bohg, S. Schaal
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
Conference on Robot Learning (CoRL), 2023
Y. Chebotar, Q. Vuong, A. Irpan, K. Hausman, F. Xia, Y. Lu, A. Kumar, T. Yu, A. Herzog, K. Pertsch, K. Gopalakrishnan, J. Ibarz, O. Nachum, S. Sontakke, G. Salazar, H. T. Tran, J. Peralta, C. Tan, D. Manjunath, J. Singht, B. Zitkovich, T. Jackson, K. Rao, C. Finn, S. Levine
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Conference on Robot Learning (CoRL), 2023
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, X. Chen, K. Choromanski, T. Ding, D. Driess, A. Dubey, C. Finn, P. Florence, C. Fu, M. Gonzalez Arenas, K. Gopalakrishnan, K. Han, K. Hausman, A. Herzog, J. Hsu, B. Ichter, A. Irpan, N. Joshi, R. Julian, D. Kalashnikov, Y. Kuang, I. Leal, L. Lee, T. E. Lee, S. Levine, Y. Lu, H. Michalewski, I. Mordatch, K. Pertsch, K. Rao, K. Reymann, M. Ryoo, G. Salazar, P. Sanketi, P. Sermanet, J. Singh, A. Singh, R. Soricut, H. Tran, V. Vanhoucke, Q. Vuong, A. Wahid, S. Welker, P. Wohlhart, J. Wu, F. Xia, T. Xiao, P. Xu, S. Xu, T. Yu, B. Zitkovich
Open-World Object Manipulation using Pre-Trained Vision-Language Models
Conference on Robot Learning (CoRL), 2023
A. Stone*, T. Xiao*, Y. Lu*, K. Gopalakrishnan, K. Lee, Q. Vuong, P. Wohlhart, B. Zitkovich, F. Xia, C. Finn, K. Hausman
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control
Neural Information Processing Systems (NeurIPS), 2023
W. Huang, F. Xia, D. Shah, A. Zeng, Y. Lu, P. Florence, I. Mordatch, S. Levine, K. Hausman, B. Ichter
PaLM-E: An Embodied Multimodal Language Model
International Conference on Machine Learning (ICML), 2023
D. Driess, F. Xia, M. Sajjadi, C. Lynch, A. Chowdhery, B. Ichter, A. Wahid, J. Tompson, Q. Vuong, T. Yu, W. Huang, Y. Chebotar, P. Sermanet, D. Duckworth, S. Levine, V. Vanhoucke, K. Hausman, M. Toussaint, K. Greff, A. Zeng, I. Mordatch, P. Florence
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
Robotics: Science and Systems (RSS), 2023
A. Herzog*, K. Rao*, K. Hausman*, Y. Lu*, P. Wohlhart*, M. Yan, J. Lin, M. Gonzalez Arenas, T. Xiao, D. Kappler, D. Ho, J. Rettinghouse, Y. Chebotar, K. Lee, K. Gopalakrishnan, R. Julian, A. Li, C. Fu, B. Wei, S. Ramesh, K. Holden, K. Kleiven, D. Rendleman, S. Kirmani, J. Bingham, J. Weisz, Y. Xu, W. Lu, M. Bennice, C. Fong, D. Do, J. Lam, Y. Bai, B. Holson, M. Quinlan, N. Brown, M. Kalakrishnan, J. Ibarz, P. Pastor, S. Levine
Scaling Robot Learning with Semantically Imagined Experience
Robotics: Science and Systems (RSS), 2023
T. Yu, T. Xiao, A. Stone, J. Tompson, A. Brohan, S. Wang, J. Singh, C. Tan, Dee M, J. Peralta, B. Ichter, K. Hausman, F. Xia
Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models
Robotics: Science and Systems (RSS), 2023
T. Xiao*, H. Chan*, P. Sermanet, A. Wahid, A. Brohan, K. Hausman, S. Levine, J. Tompson
RT-1: Robotics Transformer for Real-World Control at Scale
Robotics: Science and Systems (RSS), 2023
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu, J. Ibarz, B. Ichter, A. Irpan, T. Jackson, S. Jesmonth, N. Joshi, R. Julian, D. Kalashnikov, Y. Kuang, I. Leal, K. Lee, S. Levine, Y. Lu, U. Malla, D. Manjunath, I. Mordatch, O. Nachum, C. Parada, J. Peralta, E. Perez, K. Pertsch, J. Quiambao, K. Rao, M. Ryoo, G. Salazar, P. Sanketi, K. Sayed, J. Singh, S. Sontakke, A. Stone, C. Tan, H. Tran, V. Vanhoucke, S. Vega, Q. Vuong, F. Xia, T. Xiao, P. Xu, S. Xu, T. Yu, B. Zitkovich
Code as Policies: Language Model Programs for Embodied Control
International Conference on Robotics and Automation (ICRA), 2023
Best Learning Paper
J. Liang, W. Huang, F. Xia, P. Xu, K. Hausman, B. Ichter, P. Florence, A. Zeng
Inner Monologue: Embodied Reasoning through Planning
with Language Models

Conference on Robot Learning (CoRL), 2022
W. Huang*, F. Xia*, T. Xiao*, H. Chan, J. Liang, P. Florence, A. Zeng, J. Tompson, I. Mordatch, Y. Chebotar, P. Sermanet, N. Brown, T. Jackson, L. Luu, S. Levine, K. Hausman, B. Ichter
Offline Reinforcement Learning at Multiple Frequencies
Conference on Robot Learning (CoRL), 2022
K. Burns, T. Yu, C. Finn, K. Hausman
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Conference on Robot Learning (CoRL), 2022
Special Innovation Award
Michael Ahn*, Anthony Brohan*, Noah Brown*, Yevgen Chebotar*, Omar Cortes*, Byron David*, Chelsea Finn*, Keerthana Gopalakrishnan*, Karol Hausman*, Alex Herzog*, Daniel Ho*, Jasmine Hsu*, Julian Ibarz*, Brian Ichter*, Alex Irpan*, Eric Jang*, Rosario Jauregui Ruano*, Kyle Jeffrey*, Sally Jesmonth*, Nikhil J Joshi*, Ryan Julian*, Dmitry Kalashnikov*, Yuheng Kuang*, Kuang-Huei Lee*, Sergey Levine*, Yao Lu*, Linda Luu*, Carolina Parada*, Peter Pastor*, Jornell Quiambao*, Kanishka Rao*, Jarek Rettinghouse*, Diego Reyes*, Pierre Sermanet*, Nicolas Sievers*, Clayton Tan*, Alexander Toshev*, Vincent Vanhoucke*, Fei Xia*, Ted Xiao*, Peng Xu*, Sichun Xu*, Mengyuan Yan*
Jump-Start Reinforcement Learning
International Conference on Machine Learning (ICML), 2023
I. Uchendu, T. Xiao, Y. Lu, B. Zhu, M. Yan, J. Simon, M. Bennice, C. Fu, C. Ma, J. Jiao, S. Levine, K. Hausman
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
International Conference on Robotics and Automation (ICRA), 2023
A. Gupta, C. Lynch, B. Kinman, G. Peake, S. Levine, K. Hausman
How to Leverage Unlabeled Data in Offline Reinforcement Learning
International Conference on Machine Learning (ICML), 2022
T. Yu*, A. Kumar*, Y. Chebotar, K. Hausman, C. Finn, S. Levine
Autonomous Reinforcement Learning: Formalism and Benchmarking
International Conference on Learning Representations (ICLR), 2022
A. Sharma*, K. Xu*, N. Sardana, A. Gupta, K. Hausman, S. Levine, C. Finn
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2021
T. Yu*, A. Kumar*, Y. Chebotar, K. Hausman, S. Levine, C. Finn
Persistent Reinforcement Learning via Subgoal Curricula
Neural Information Processing Systems (NeurIPS), 2021
A. Sharma, A. Gupta, S. Levine, K. Hausman, C. Finn
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
Conference on Robot Learning (CoRL), 2021
D. Kalashnikov*, J. Varley*, Y. Chebotar, B. Swanson, R. Jonschkowski, C. Finn, S. Levine, K. Hausman*
AW-Opt: Learning Robotic Skills with Imitation and Reinforcement Learning at Scale
Conference on Robot Learning (CoRL), 2021
Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
International Conference on Machine Learning (ICML), 2021
Y.Chebotar, K. Hausman, Y. Lu, T. Xiao, D. Kalashnikov, J. Varley, A. Irpan, B. Eysenbach, R. Julian, C. Finn, S. Levine
A Geometric Perspective on Self-Supervised Policy Adaptation
International Conference on Robotics and Automation (ICRA), 2020
C. Bodnar, K. Hausman, G. Dulac-Arnold, R. Jonschkowski
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
Conference on Robot Learning (CoRL), 2020
R. Julian, B. Swanson, G. Sukhatme, S. Levine, C. Finn, K. Hausman
Modeling Long-horizon Tasks as Sequential Interaction Landscapes
Conference on Robot Learning (CoRL), 2020
S. Pirk, K. Hausman, A. Toshev, M. Khansari
Gradient Surgery for Multi-Task Learning
Neural Information Processing Systems (NeurIPS), 2020
T. Yu, S. Kumar, A. Gupta, S. Levine, K. Hausman, C. Finn
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping
Robotics: Science and Systems (RSS), 2020
Best Systems Paper Finalist
C. Bodnar, A. Li, K. Hausman, P. Pastor, M. Kalakrishnan
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
Robotics: Science and Systems (RSS), 2020
A. Sharma, M. Ahn, S. Levine, V. Kumar, K. Hausman*, S. Gu*
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control
International Conference on Learning Representations (ICLR), 2020
T. Xiao, E. Jang, D. Kalashnikov, S. Levine, J. Ibarz, K. Hausman*, A. Herzog*
Dynamics-Aware Unsupervised Discovery of Skills
International Conference on Learning Representations (ICLR), 2020
oral presentation
A. Sharma, S. Gu, S. Levine, V. Kumar, K. Hausman
Learning to Interactively Learn and Assist
AAAI 2020,
oral presentation
M. Woodward, C. Finn, K. Hausman
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
Conference on Robot Learning (CoRL), 2019
A. Gupta, V. Kumar, C. Lynch, S. Levine, K. Hausman
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Conference on Robot Learning (CoRL), 2019
T. Yu, D. Quillen, Z. He, R. Julian, K. Hausman, C. Finn, S. Levine
Scaling Simulation-to-real Transfer by Learning Composable Robot Skills.
International Symposium on Experimental Robotics (ISER), 2018
International Journal of Robotics Research (IJRR), 2019
R. Julian*, E. Heiden*, Z. He, H. Zhang,
S. Schaal, J. Lim, G. Sukhatme, K. Hausman

Learning an Embedding Space for Transferable Robot Skills
International Conference on Learning Representations (ICLR), 2018
K. Hausman, J.T. Springenberg, Z. Wang, N. Heess, M. Riedmiller
Multi-Modal Imitation Learning from Unstructured Demonstrations using GANs
Neural Information Processing Systems (NIPS), 2017
K. Hausman*, Y. Chebotar*, S. Schaal, G. Sukhatme, J. Lim
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
International Conference on Machine Learning (ICML), 2017
Y. Chebotar*, K. Hausman*, M. Zhang*, G. Sukhatme, S. Schaal, S. Levine
Generalizing Regrasping with Supervised Policy Learning
International Symposium on Experimental Robotics (ISER), 2016          
Y. Chebotar*, K. Hausman*, O. Kroemer, G. Sukhatme, S. Schaal
Self-Supervised Regrasping using Spatio-Temporal Tactile Features and Reinforcement Learning
International Conference on Intelligent Robots and Systems (IROS), 2016
Y. Chebotar, K. Hausman, Z. Su, G. Sukhatme, S. Schaal

Workshop Publications

Training an Interactive Helper
NIPS Workshop on Emergent Communication and NIPS Workshop Learning by Instruction, 2018
M. Woodward, C. Finn, K. Hausman pdf

Learning a System-ID Embedding Space for Domain Specialization
with Deep Reinforcement Learning

NIPS Workshop on Reinforcement Learning under Partial Observability, 2018
J. Preiss, K. Hausman, G. Sukhatme pdf

Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing
NIPS Deep Reinforcement Learning Workshop, 2018
Z. He, R. Julian, E. Heiden, H. Zhang, S. Schaal, J. Lim, G. Sukhatme, K. Hausman pdf

Learning Skill Embeddings for Transferable Robot Skills
NIPS Deep Reinforcement Learning Symposium, 2017
K. Hausman, J.T. Springenberg, Z. Wang, N. Heess, M. Riedmiller pdf

Learning Robot Skill Embeddings
NIPS Workshop on Acting and Interacting in the Real World: Challenges in Robot Learning, 2017
K. Hausman, J.T. Springenberg, Z. Wang, N. Heess, M. Riedmiller pdf

IntentionGAN: Multi-Task Imitation Learning from Unstructured Demonstrations
Conference on Robot Learning (CoRL), 2017
K. Hausman*, Y. Chebotar*, S. Schaal, G. Sukhatme, J. Lim bibtex pdf

IntentionGAN: Multi-Modal Imitation Learning from Unstructured Demonstrations
RSS Workshop on Learning from Demonstration in High-Dimensional Feature Spaces, 2017
K. Hausman*, Y. Chebotar*, S. Schaal, G. Sukhatme, J. Lim bibtex pdf

Combining Model-Based and Model-Free Updates for Deep Reinforcement Learning
RSS Workshop on New Frontiers for Deep Learning in Robotics, 2017
Best Paper Award
Y. Chebotar*, K. Hausman*, M. Zhang*, G. Sukhatme, S. Schaal, S. Levine bibtex pdf

Regrasping using Tactile Perception and Supervised Policy Learning
AAAI Symposium on Interactive Multi-Sensory Object Perception for Embodied Agents, 2017
Y. Chebotar, K. Hausman, Z. Su, G. Sukhatme, S. Schaal bibtex pdf

Supervised Policy Fusion with Application to Regrasping
IROS Workshop on Closed-loop Grasping and Manipulation: Challenges and Progress, 2016
Y. Chebotar*, K. Hausman*, O. Kroemer, G. Sukhatme, S. Schaal bibtex pdf




Interactive Perception

In interactive perception (IP) any kind of forceful interactions with the environment are used to simplify and enhance perception, in turn enabling robust perceptually-guided manipulation. IP has two main benefits: i) physical interaction creates a novel sensory signal that would otherwise not be present, and ii) by exploiting knowledge of the regularity in the combined space of sensory data and action parameters, the prediction and interpretation of this novel signal becomes simpler and more robust. For more details, see our survey paper.

Interactive Perception: Leveraging Action in Perception and Perception in Action
IEEE Transactions on Robotics (T-RO), 2016
J. Bohg*, K. Hausman*, B. Sankaran*, O. Brock, D. Kragic, S. Schaal, G. Sukhatme
Active Articulation Model Estimation through Interactive Perception    
International Conference on Robotics and Automation (ICRA), 2015
K. Hausman, S. Niekum, S. Osentoski , G. Sukhatme
Force Estimation and Slip Detection for Grip Control using a Biomimetic Tactile Sensor
International Conference on Humanoid Robotics (Humanoids), 2015
Z. Su, K. Hausman, Y. Chebotar, A. Molchanov, G. Loeb, G. Sukhatme, S. Schaal
Interactive Segmentation of Textured and Textureless Objects
Chapter in Handling Uncertainty and Networked Structure in Robot Control, L. Busoniu and L. Tamas (eds.), Springer, 2015
K. Hausman, D. Pangercic, Z. Marton, F. Belent-Benczedi, C. Bersch, M. Gupta, G. Sukhatme, M. Beetz
Tracking-based Interactive Segmentation of Textureless Objects
International Conference on Robotics and Automation (ICRA), 2013
Best Service Robotics Paper Finalist
K. Hausman, F. Balint-Benczedi, D. Pangercic, Z. Marton,
R. Ueda, K. Okada, M. Beetz

Workshop Publications

BiGS: BioTac Grasp Stability Dataset
ICRA Workshop on Grasping and Manipulation Datasets, 2016
Y. Chebotar, K. Hausman, Z. Su, A. Molchanov, O. Kroemer, G. Sukhatme, S. Schaal
website bibtex pdf

Slip Classification Using Tangential and Torsional Skin Distortions
on a Biomimetic Tactile Sensor

BMVA Workshop on Visual, Tactile and Force Sensing for Robot Manipulation, 2015
Z. Su, K. Hausman, Y. Chebotar, A. Molchanov, G. Loeb, G. Sukhatme, S. Schaal bibtex pdf

Slip Detection and Classification for Grip Control using Multiple Sensory Modalities
on a Biomimetic Tactile Sensor

IROS Workshop on Multimodal Sensor-Based Robot Control for HRI and Soft Manipulation, 2015
Z. Su, K. Hausman, Y. Chebotar, A. Molchanov, G. Loeb, G. Sukhatme, S. Schaal bibtex pdf

Towards Interactive Object Recognition
IROS 3rd Workshop on Robots in Clutter: Perception and Interaction in Clutter, 2014
K. Hausman, C. Corcos, J. Mueller, F. Sha, G. Sukhatme bibtex pdf

Segmentation of Cluttered Scenes through Interactive Perception
ICRA Workshop on Semantic Perception and Mapping for Knowledge-enabled Service Robotics, 2012
K. Hausman, C. Bersch, D. Pangercic, S. Osentoski, Z. Marton, M. Beetz bibtex pdf

Segmentation of Textured and Textureless Objects through Interactive Perception
RSS Workshop on Robots in Clutter: Manipulation, Perception and Navigation in Human Environments, 2012
C. Bersch, D. Pangercic, S. Osentoski, K. Hausman, Z. Marton, R. Ueda, K. Okada, M. Beetz bibtex pdf




Active Perception

Active perception pioneered the insight that perception is active and exploratory. In my research, I try to show that, state estimation (perception) can be significantly improved when considered jointly with control (action). I demonstrate these research insights on various flying vehicles such as quadrotors.

Simultaneous Self-Calibration and Navigation using Trajectory Optimization
International Journal of Robotics Research (IJRR), 2018
J. Preiss, K. Hausman, G. Sukhatme, S. Weiss
Confidence-rich Grid Mapping
International Symposium on Robotics Research (ISRR), 2017
International Journal of Robotics Research (IJRR), 2019
A. Agha-mohammadi, E. Heiden, K. Hausman, G. Sukhatme
Trajectory Optimization for Self-Calibration and Navigation      
Robotics: Science and Systems (RSS), 2017
J. Preiss, K. Hausman, G. Sukhatme, S. Weiss
Planning High-speed Safe Trajectories in Confidence-rich Map
International Conference on Intelligent Robots and Systems (IROS), 2017
E. Heiden, K. Hausman, G. Sukhatme, A. Agha-mohammadi
Observability-Aware Trajectory Optimization for Self-Calibration with Application to UAVs
Robotics and Automation Letter (RA-L), 2017
K. Hausman, J. Preiss, G. Sukhatme, S. Weiss
Occlusion-Aware Multi-Robot 3D Tracking
International Conference on Intelligent Robots and Systems (IROS), 2016
K. Hausman, G. Kahn, S. Patil, J. Mueller, K. Goldberg, P. Abbeel, G. Sukhatme
Cooperative Multi-Robot Control for Target Tracking with Onboard Sensing
International Journal of Robotics Research (IJRR), 2015
K. Hausman, J. Mueller, A. Hariharan, N. Ayanian, G. Sukhatme
Self-Calibrating Multi-Sensor Fusion with Probabilistic Measurement Validation for Seamless Sensor Switching on a UAV
International Conference on Robotics and Automation (ICRA), 2016
K. Hausman, S. Weiss, R. Brockers, L. Matthies, G. Sukhatme
Cooperative Control for Target Tracking with Onboard Sensing      
International Symposium on Experimental Robotics (ISER), 2014
K. Hausman, J. Mueller, A. Hariharan, N.Ayanian, G. Sukhatme

Workshop Publications

Confidence-aware Occupancy Grids
IROS Workshop on Vision-based Agile Autonomous Navigation of UAVs, 2017
A. Agha-mohammadi, E. Heiden, K. Hausman, G. Sukhatme bibtex pdf

High-speed Safe Trajectory Planning in Confidence-rich Maps
IROS Workshop on Vision-based Agile Autonomous Navigation of UAVs, 2017
E. Heiden, K. Hausman, G. Sukhatme, A. Agha-mohammadi bibtex pdf

Observability-Aware Trajectory Optimization for Self-Calibration with Application to UAVs
RSS Workshop on Robot-Environment Interaction for Perception and Manipulation, 2016
K. Hausman, J. Preiss, G. Sukhatme, S. Weiss bibtex pdf

Optimization-based Cooperative Multi-Robot Target Tracking
with Reasoning about Occlusions

IROS Workshop on On-line Decision-Making in Multi-Robot Coordination, 2015
K. Hausman, G. Kahn, S. Patil, J. Mueller, K. Goldberg, P. Abbeel, G. Sukhatme bibtex pdf

Cooperative Multi-Robot Control for Target Tracking
with Efficient Switching of Onboard Sensing Topologies

IROS Workshop on Taxonomies of Interconnected Systems:
Topology in Distributed Robotics, 2014
K. Hausman, J. Mueller, A. Hariharan, N. Ayanian, G. Sukhatme bibtex pdf