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Roberto Calandra
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning

Dec 16, 2020
Nathan O. Lambert, Albert Wilcox, Howard Zhang, Kristofer S. J. Pister, Roberto Calandra

* 8 pages, +2 pages appendix 
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TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors

Dec 15, 2020
Shaoxiong Wang, Mike Lambeta, Po-Wei Chou, Roberto Calandra


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Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion

Sep 18, 2020
Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai


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Active MR k-space Sampling with Reinforcement Learning

Jul 20, 2020
Luis Pineda, Sumana Basu, Adriana Romero, Roberto Calandra, Michal Drozdzal

* To appear in 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020 
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3D Shape Reconstruction from Vision and Touch

Jul 07, 2020
Edward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal

* Submitted for review 
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Learning Invariant Representations for Reinforcement Learning without Reconstruction

Jun 18, 2020
Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine


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Learning to Play Table Tennis From Scratch using Muscular Robots

Jun 10, 2020
Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters

* 11 pages, 8 figures. Submitted to T-RO. For more information visit https://muscularTT.embodied.ml 
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DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation

May 29, 2020
Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra

* 8 pages, published in the IEEE Robotics and Automation Letters (RA-L) 
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Plan2Vec: Unsupervised Representation Learning by Latent Plans

May 07, 2020
Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

* Proceedings of Machine Learning Research, the 2nd Annual Conference on Learning for Dynamics and Control (2020) Volume 120, 1-12 
 * code available at https://geyang.github.io/plan2vec 
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Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads

Apr 23, 2020
Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine


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Adversarial Continual Learning

Mar 21, 2020
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, Marcus Rohrbach


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OmniTact: A Multi-Directional High Resolution Touch Sensor

Mar 16, 2020
Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine

* Accepted at International Conference on Robotics and Automation (ICRA) 2020 
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Objective Mismatch in Model-based Reinforcement Learning

Feb 11, 2020
Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra

* 8 pages, 2 pages references, 5 pages appendices 
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Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization

Jan 31, 2020
Benjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy


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Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning

Nov 15, 2019
Kevin Sebastian Luck, Heni Ben Amor, Roberto Calandra

* Accepted for the Conference on Robot Learning 2019 
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Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning

Sep 26, 2019
Tianyu Li, Nathan Lambert, Roberto Calandra, Franziska Meier, Akshara Rai

* Submitted to 2020 ICRA 
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Data-efficient Learning of Morphology and Controller for a Microrobot

May 03, 2019
Thomas Liao, Grant Wang, Brian Yang, Rene Lee, Kristofer Pister, Sergey Levine, Roberto Calandra

* Accepted at ICRA-2019. 6 pages 
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Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots

Apr 07, 2019
Dieter Büchler, Roberto Calandra, Jan Peters

* 12 pages, preprint submitted to Journal of Robotics and Autonomous Systems 
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Manipulation by Feel: Touch-Based Control with Deep Predictive Models

Mar 11, 2019
Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine

* Accepted to ICRA 2019 
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Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching

Mar 08, 2019
Justin Lin, Roberto Calandra, Sergey Levine

* 6 pages; accepted to IEEE International Conference on Robotics and Automation 2019 (ICRA 2019) 
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Fast Neural Network Verification via Shadow Prices

Mar 08, 2019
Vicenc Rubies-Royo, Roberto Calandra, Dusan M. Stipanovic, Claire Tomlin


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Low Level Control of a Quadrotor with Deep Model-Based Reinforcement learning

Jan 11, 2019
Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli, Roberto Calandra, Sergey Levine, Kristofer S. J. Pister

* 10 pages, 12 figures 
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Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

Nov 02, 2018
Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine

* NIPS 2018, video and code available at https://sites.google.com/view/drl-in-a-handful-of-trials/ 
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More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch

Jul 26, 2018
Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine

* 8 pages. Published on IEEE Robotics and Automation Letters (RAL). Website: https://sites.google.com/view/more-than-a-feeling 
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Learning Flexible and Reusable Locomotion Primitives for a Microrobot

Mar 01, 2018
Brian Yang, Grant Wang, Roberto Calandra, Daniel Contreras, Sergey Levine, Kristofer Pister

* 8 pages. Accepted at RAL+ICRA2018 
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MBMF: Model-Based Priors for Model-Free Reinforcement Learning

Oct 17, 2017
Somil Bansal, Roberto Calandra, Kurtland Chua, Sergey Levine, Claire Tomlin

* After we submitted the paper for consideration in CoRL 2017 we found a paper published in the recent past with a similar method (see related work for a discussion). Considering the similarities between the two papers, we have decided to retract our paper from CoRL 2017 
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The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?

Oct 16, 2017
Roberto Calandra, Andrew Owens, Manu Upadhyaya, Wenzhen Yuan, Justin Lin, Edward H. Adelson, Sergey Levine

* 10 pages, accepted at the 1st Annual Conference on Robot Learning (CoRL) 
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Goal-Driven Dynamics Learning via Bayesian Optimization

Sep 22, 2017
Somil Bansal, Roberto Calandra, Ted Xiao, Sergey Levine, Claire J. Tomlin

* This is the extended version of the CDC'17 paper titled "Goal-Driven Dynamics Learning via Bayesian Optimization." 
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