About Me
Ajay Kumar Tanwani
Postdoctoral scholar,
University of California, Berkeley
Ph.D. in CS, EPFL | MS in Robotics, EMARO | Intern, Google X
Email: ajay.tanwani at berkeley.edu, aktanwani at gmail.com
Research Interests
I work with Ken Goldberg in AutoLab and BAIR on scalable robot imitation and representation learning over Fog/Cloud. My interests broadly revolve around developing machine learning technqiues for solving real-world problems. The main scientific subjects I investigate include:
|
|
|
|
|
|
Recent News
Please visit From Cloud to Fog Robotics for details on Fog Robotics.
Two papers on imitation learning have been accepted at WAFR 2018. [coming soon]
Small Variance Asymptotics for Non-Parametric Online Robot Learning is accepted at Int. J. of Robotics Research (IJRR) 2018.
We participated in the Fog Congress 2018 organized by the Open Fog consortium.
Our NSF Proposal on Fog Robotics has been accepted, in collaboration with SwarmLab and RiseLab. [3 million USD for 3 years]
New York Times article on How Robot Hands are Evolving to Do What Ours Can by Mae Rayan, Cade Metz, and Rumsey Taylor. Our work on the gripper, the picker and the bed-maker is featured against the OpenAI dactyl and anthropomorphic UW hand.
We won the initial round of HSR Home Chores Challenge 2018 [video], and are runners-up in TRI University Challenge 2018 and Siemens FutureMaker Challenge 2018. [see relevance to SCHooL]
Dexterous Underwater Manipulation from Distant Onshore Locations is accepted for publication in IEEE Robotics and Automation Magazine.
We presented two papers on imitation learning in Imitation and Causality Workshop, RSS 2018.
Dex-Net as a Service (DNaaS) is now available online for computing and visualizing robust grasps.
I moved to UC Berkeley for postdoctoral research.
I defended my PhD thesis at EPFL. Thanks to all the jury members !
I joined the program committee of NIPS 2018, RSS 2018, AABI (NIPS) 2017.
I finished my internship at Google X in Mountain View, California, 2017.
Publications
- Ajay Kumar Tanwani, Sylvain Calinon. Small Variance Asymptotics for Non-Parametric Online Robot Learning. International Journal of Robotics and Research, 2018
[pdf] [bibtex] [video1] [video2]
- Pusong Li, Bill DeRose, Jeffrey Mahler, Juan Aparicio Ojea, Ajay Kumar Tanwani, Ken Goldberg. Dex-Net as a Service (DNaaS): A Cloud-Based Robust Robot Grasp Planning System. IEEE International Conference on Automation Science and Engineering (CASE), 2018
[pdf] [bibtex] [website] [media]
- A. Birk, T. Fromm, C.A. Mueller, T. Luczynski, A.G. Chavez, D. Koehntopp, A. Kupcsik, S. Calinon, A.K. Tanwani, G. Antonelli, P. di Lillo, E. Simetti, G. Casalino, G. Indiveri, L. Ostuni, A. Turetta, A. Caffaz, P. Weiss, T. Gobert, B. Chemisky, J. Gancet, T. Siedel, S. Govindaraj, X. Martinez, and P. Letier. Dexterous Underwater Manipulation from Distant Onshore Locations. IEEE Robotics and Automation Magazine, 2018
[pdf] [bibtex]
- Ajay Kumar Tanwani, Jonathon Lee, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg. Robot Learning with Invariant Hidden Semi-Markov Models. Imitation and Causality Workshop: Robotics, Science and Systems, 2018
[pdf] [bibtex] [poster]
- Jonathon Lee, Michael Laskey, Ajay Kumar Tanwani, Ken Goldberg. Stability Analysis of On-Policy Imitation Learning Algorithms Using Dynamic Regret . Imitation and Causality Workshop: Robotics, Science and Systems, 2018
[pdf] [bibtex] [poster]
- [PhD Thesis] Ajay Kumar Tanwani. Generative Models for Learning Robot Manipulation Skills from Humans . PhD Thesis, Ecole Polytechnique Federale de Lausanne, EPFL, 2018
[pdf] [multimedia] [bibtex]
- Ajay Kumar Tanwani, Sylvain Calinon. A Generative Model for Intention Recognition and Manipulation Assistance in Teleoperation . IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017
[pdf] [bibtex] [video1] [video2] [media]
- Ajay Kumar Tanwani, Sylvain Calinon. Small Variance Asymptotics for Non-Parametric Online Robot Learning. arXiv:1610.02468, 2016
[pdf] [bibtex] [video1] [video2]
- Ajay Kumar Tanwani, Sylvain Calinon. Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics . NIPS workshop on Advances in Approximate Bayesian Inference, 2016
[pdf] [bibtex] [poster]
- J. Gancet, P. Weiss, G. Antonelli, MF. Pfingsthorn, S. Calinon, A. Turetta, C. Walen, D. Urbina, S. Govindaraj, P. Letier, X. Martinez, J. Salini, B. Chemisky, G. Indiveri, G. Casalino, P. Di Lillo, E. Simetti, D. De Palma, A. Birk, A. K. Tanwani, I. Havoutis, A. Caffaz, L. Guilpain. Dexterous Undersea Interventions with Far Distance Onshore Supervision: the DexROV Project . IFAC Conference on Control Applications in Marine Systems (CAMS), 2016
[pdf] [bibtex] [video]
- Ioannis Havoutis, Ajay Kumar Tanwani and Sylvain Calinon, Online Incremental Learning of Manipulation Tasks for Semi-Autonomous Teleoperation . IEEE/RSJ IROS Workshop on Closed-loop Grasping and Manipulation, 2016
[pdf] [bibtex] [video]
- [Best Manipulation Paper Award Finalist at ICRA 2016] Ajay Kumar Tanwani, Sylvain Calinon. Learning Robot Manipulation Tasks with Task-Parameterized Semi-Tied Hidden Semi-Markov Model. IEEE Robotics and Automation Letters (RA-L), vol. 1 (1), pp. 235-242, 2016. presented in International Conference on Robotics and Automation (ICRA) 2016
[pdf] [bibtex] [video] [codes] [slides] [media1][media2]
- Ajay Kumar Tanwani. Learning Robot Manipulation Tasks with Semi-Tied Gaussian Mixture Models. Swiss Machine Learning Day, EPFL, 2015
[link] [slides]
- J. Gancet, D. Urbina, P. Letier, M. Ilzokvitz, P. Weiss, F. Gauch, G. Antonelli, G. Indiveri, G. Casalino, A. Birk, MF. Pfingsthorn, S. Calinon, A. K. Tanwani, A. Turetta, C. Walen, L. Guilpain. DexROV: Dexterous Undersea Inspection and Maintenance in Presence of Communication Latencies. IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles (NGCUV), 2015
[pdf] [bibtex] [video]
- Ajay Kumar Tanwani, José del R. Millán, Aude Billard. Rewards-Driven Control of Robot Arm by Decoding EEG Signals. IEEE Engineering in Medicine and Biology Society Conference (EMBC), 2014
[pdf] [bibtex] [slides]
- Ajay Kumar Tanwani, Aude Billard. Transfer in Inverse Reinforcement Learning for Multiple Strategies. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013
[pdf] [bibtex] [video] [slides]
- Ajay Kumar Tanwani, Aude Billard. Inverse Reinforcement Learning for Compliant Manipulation in Letter Handwriting. National Center of Competence in Robotics Research (NCCR) Review, 2013
[poster]
- Pawel Wawrzynski, Ajay Kumar Tanwani. Autonomous reinforcement learning with experience replay. Neural Networks, Elsevier, 2013
[pdf] [bibtex]
- Ajay Kumar Tanwani. Optimizing walking of a humanoid robot using reinforcement learning. MS Thesis, European Masters on Advanced Robotics (EMARO), Nov 2011
[pdf] [bibtex] [video]
- Ajay Kumar Tanwani, Muddassar Farooq, Classification potential vs classification accuracy: a comprehensive study of evolutionary algorithms with biomedical datasets. J. Bacardit et al. (Eds), Learning Classifier Systems (LCS), Springer LNAI, 2010
[pdf] [bibtex]
- Ajay Kumar Tanwani, Jamal Afridi, Zubair Shafique and Muddassar Farooq. Guidelines to select machine learning scheme for classification of biomedical datasets. 7th European Conference on Evolutionary Computation, Machine Learning and Datamining (EvoBIO), Springer LNCS, 2009
[pdf] [bibtex]
- Ajay Kumar Tanwani, Muddassar Farooq. The role of biomedical dataset in classification. Artificial Intelligence in Medicine (AIME), Springer LNAI, 2009
[pdf] [bibtex]
- Syed Bilal Mehdi, Ajay Kumar Tanwani, Muddassar Farooq. IMAD: In-execution malware analysis and detection. Genetic and Evolutionary Computation Conference (GECCO), 2009
[pdf] [bibtex]
- Ajay Kumar Tanwani, Muddassar Farooq. Performance evaluation of evolutionary algorithms in classification of biomedical datasets. International Workshop on Learning Classifier Systems, IWLCS (GECCO), 2009
[pdf] [bibtex]
- Amina Tariq, Ajay Kumar Tanwani and Muddassar Farooq. User-centered design for mobile healthcare application in conservative environments. 10th Annual Conference of the NZ group on Human Computer Interaction, CHI-NZ, 2009
[pdf] [bibtex]