From Computational Learning and Motor Control Lab

Main: Yevgen Chebotar

Yevgen Chebotar is a Ph.D. candidate at the University of Southern California in the Computational Learning and Motor Control Lab (CLMC) advised by Prof. Stefan Schaal and Prof. Gaurav Sukhatme. Before joining CLMC, Yevgen received his B.Sc. and M.Sc. degrees in Computer Science from the Technical University of Darmstadt. During his Ph.D., Yevgen did a number of internships, including X, Google Brain and Nvidia Robotics. His research focuses on machine learning for robotics, with an emphasis on reinforcement, imitation and transfer learning for efficient acquisition of sensory-based robotic skills.

Research Interests:
Reinforcement Learning, Imitation Learning, Transfer Learning, Deep Learning, Computer Vision, Tactile Perception

Curriculum Vitae | Google Scholar | E-Mail -> mailto:ychebota [snail] usc [period] edu

Projects

Publications

Conference papers

Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk, Miles Macklin, Jan Issac, Nathan Ratliff, Dieter Fox. arXiv:1810.05687, 2018. [pdf] [arXiv] [video]

Time-Contrastive Networks: Self-Supervised Learning from Video
Pierre Sermanet*, Corey Lynch*, Yevgen Chebotar*, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine. In IEEE International Conference on Robotics and Automation (ICRA), 2018. [pdf] [arXiv] [video]

Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets
Karol Hausman*, Yevgen Chebotar*, Stefan Schaal, Gaurav Sukhatme, Joseph Lim. In Neural Information Processing Systems (NIPS), 2017. [pdf] [arXiv] [video]

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
Yevgen Chebotar*, Karol Hausman*, Marvin Zhang*, Gaurav Sukhatme, Stefan Schaal, Sergey Levine. In International Conference on Machine Learning (ICML), 2017. [pdf] [arXiv] [video]

Path Integral Guided Policy Search
Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, Sergey Levine. In IEEE International Conference on Robotics and Automation (ICRA), 2017. [pdf] [arXiv] [video] [blog]

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search
Ali Yahya, Adrian Li, Mrinal Kalakrishnan, Yevgen Chebotar, Sergey Levine. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017. [pdf] [arXiv] [video] [blog]

Generalizing Regrasping with Supervised Policy Learning
Yevgen Chebotar*, Karol Hausman*, Oliver Kroemer, Gaurav Sukhatme, Stefan Schaal. In International Symposium on Experimental Robotics (ISER), 2016. [pdf] [video]

Self-Supervised Regrasping using Spatio-Temporal Tactile Features and Reinforcement Learning
Yevgen Chebotar, Karol Hausman, Zhe Su, Gaurav Sukhatme, Stefan Schaal. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016. [pdf] [video]

Distilling Knowledge from Ensembles of Neural Networks for Speech Recognition
Yevgen Chebotar, Austin Waters. In Interspeech, 2016. [pdf]

Force Estimation and Slip Detection for Grip Control using a Biomimetic Tactile Sensor
Zhe Su, Karol Hausman, Yevgen Chebotar, Artem Molchanov, Gerald Loeb, Gaurav Sukhatme, Stefan Schaal. In IEEE-RAS International Conference on Humanoid Robotics (Humanoids), 2015. [pdf]

Learning Robot Tactile Sensing for Object Manipulation
Yevgen Chebotar, Oliver Kroemer, Jan Peters. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014. [pdf]

Behind the article: Recognizing dialog acts in Wikipedia talk pages
Oliver Ferschke, Iryna Gurevych, Yevgen Chebotar. In 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2012. [pdf]

Workshops

Combining Model-Based and Model-Free Updates for Deep Reinforcement Learning
Yevgen Chebotar*, Karol Hausman*, Marvin Zhang*, Gaurav Sukhatme, Stefan Schaal, Sergey Levine. Best Paper Award at RSS 2017 Workshop on New Frontiers for Deep Learning in Robotics, 2017. [pdf] [arXiv] [video]

Supervised Policy Fusion with Application to Regrasping
Yevgen Chebotar*, Karol Hausman*, Oliver Kroemer, Gaurav Sukhatme, Stefan Schaal, In IROS 2016 Workshop on Closed-loop Grasping and Manipulation: Challenges and Progress, 2016. [pdf]

BiGS: BioTac Grasp Stability Dataset
Yevgen Chebotar, Karol Hausman, Zhe Su, Artem Molchanov, Oliver Kroemer, Gaurav Sukhatme, Stefan Schaal, In ICRA 2016 Workshop on Grasping and Manipulation Datasets, 2016. [pdf] [dataset]

Slip Classification Using Tangential and Torsional Skin Distortions on a Biomimetic Tactile Sensor
Zhe Su, Karol Hausman, Yevgen Chebotar, Artem Molchanov, Gerald Loeb, Gaurav Sukhatme, Stefan Schaal, In BMVA Workshop on Visual, Tactile and Force Sensing for Robot Manipulation, 2015. [pdf]

Slip Detection and Classification for Grip Control using Multiple Sensory Modalities on a Biomimetic Tactile Sensor
Zhe Su, Karol Hausman, Yevgen Chebotar, Artem Molchanov, Gerald Loeb, Gaurav Sukhatme, Stefan Schaal, In IROS 2015 Workshop on Multimodal Sensor-Based Robot Control for HRI and Soft Manipulation, 2015. [pdf]


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