CoRL

The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learning

Jan Blumenkamp, Amanda Prorok

Comments Accepted to Conference on Robot Learning (CoRL) 2020. Camera-ready version incorporating rebuttal

Unsupervised Metric Relocalization Using Transform Consistency Loss

Mike Kasper, Fernando Nobre, Christoffer Heckman, Nima Keivan

Comments Accepted for publication in the 4th Conference on Robot Learning (CoRL 2020), Cambridge MA, USA

TartanVO: A Generalizable Learning-based VO

Wenshan Wang, Yaoyu Hu, Sebastian Scherer

Journal ref The Conference on Robot Learning 2020

High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards

Kai Ploeger, Michael Lutter, Jan Peters

Comments Published at Conference on Robot Learning (CoRL) 2020

SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving

Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Cowen Rivers, Zheng Tian, Daniel Palenicek, Haitham bou Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang

Comments 20 pages, 11 figures. Paper accepted to CoRL 2020

ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representations

Samuel Pfrommer, Mathew Halm, Michael Posa

Comments S.P. and M.H. contributed equally to this work; Accepted to CoRL 2020

Learning Vision-based Reactive Policies for Obstacle Avoidance

Elie Aljalbout, Ji Chen, Konstantin Ritt, Maximilian Ulmer, Sami Haddadin

Comments Accepted for publication at CoRL 2020

COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning

Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine

Comments Accepted to CoRL 2020. Source code and videos available at https://sites.google.com/view/cog-rl

Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds

Tai Wang, Xinge Zhu, Dahua Lin

Comments Conference on Robot Learning (CoRL) 2020

The RobotSlang Benchmark: Dialog-guided Robot Localization and Navigation

Shurjo Banerjee, Jesse Thomason, Jason J. Corso

Comments Conference on Robot Learning 2020

Modeling Long-horizon Tasks as Sequential Interaction Landscapes

Sören Pirk, Karol Hausman, Alexander Toshev, Mohi Khansari

Comments Published at 4th Conference on Robot Learning (CoRL 2020), Cambridge MA, USA More details available at: http://www.pirk.io

CLOUD: Contrastive Learning of Unsupervised Dynamics

Jianren Wang, Yujie Lu, Hang Zhao

Journal ref CORL 2020

Accelerating Reinforcement Learning with Learned Skill Priors

Karl Pertsch, Youngwoon Lee, Joseph J. Lim

Comments 4th Conference on Robot Learning (CoRL), 2020

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments

Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert

Comments Published at the Conference on Robot Learning (CoRL) 2020

Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control

Guangzhi Tang, Neelesh Kumar, Raymond Yoo, Konstantinos P. Michmizos

Comments Conference on Robot Learning (CoRL) 2020, 14 pages, 7 figures

Dynamic Experience Replay

Jieliang Luo, Hui Li

Comments 10 pages, 5 figures, presented at 2019 Conference on Robot Learning (CoRL)

Journal ref PMLR 100:1191-1200, 2020

Learning to Manipulate Object Collections Using Grounded State Representations

Matthew Wilson, Tucker Hermans

Comments Accepted to Conference on Robot Learning 2019 (Oral); Video results: https://bit.ly/2khSKUs; v3: fix abstract and appendix

Concurrent Training Improves the Performance of Behavioral Cloning from Observation

Zachary W. Robertson, Matthew R. Walter

Comments 13 pages, 2 figures, Submitted to the 4th Conference on Robot Learning (CoRL 2020)

Combining Deep Learning and Verification for Precise Object Instance Detection

Siddharth Ancha, Junyu Nan, David Held

Comments 9 pages main paper, 2 pages references, 10 pages supplementary material

Journal ref Conference on Robot Learning (CoRL), 2019

Energy-Based Hindsight Experience Prioritization

Rui Zhao, Volker Tresp

Comments Published in Conference on Robot Learning (CoRL 2018) as oral presentation (7%), Zurich, Switzerland

Journal ref PMLR 87:113-122, 2018

On-Policy Robot Imitation Learning from a Converging Supervisor

Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Felix Li, Arsh Zahed, Joseph E. Gonzalez, Ken Goldberg

Comments Conference on Robot Learning (CoRL) 2019 Oral. First two authors contributed equally

Journal ref 3rd Conference on Robot Learning (CoRL 2019)

Entity Abstraction in Visual Model-Based Reinforcement Learning

Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine

Comments Accepted at CoRL 2019

Stochastic Optimal Control as Approximate Input Inference

Joe Watson, Hany Abdulsamad, Jan Peters

Comments Conference on Robot Learning (CoRL 2019)

Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation

Kuan Fang, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei

Comments CoRL 2019

Adversarial Active Exploration for Inverse Dynamics Model Learning

Zhang-Wei Hong, Tsu-Jui Fu, Tzu-Yun Shann, Yi-Hsiang Chang, Chun-Yi Lee

Comments Published as a conference paper at CoRL 2019

Certified Adversarial Robustness for Deep Reinforcement Learning

Björn Lütjens, Michael Everett, Jonathan P. How

Comments Published at Conference on Robot Learning (CoRL) 2019; (v2) contains minor updates to related works; (v3) acknowledged AWS

Journal ref Proceedings of Machine Learning Research (PMLR) Vol. 100, 2019

Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards

Rituraj Kaushik, Konstantinos Chatzilygeroudis, Jean-Baptiste Mouret

Comments Conference on Robot Learning (CoRL)- 2018; Code at https://github.com/resibots/kaushik_2018_multi-dex ; Video at https://youtu.be/9ZLwUxAAq6M

Journal ref Proceedings of the Conference on Robot Learning, PMLR 87:839-855, 2018

TuneNet: One-Shot Residual Tuning for System Identification and Sim-to-Real Robot Task Transfer

Adam Allevato, Elaine Schaertl Short, Mitch Pryor, Andrea L. Thomaz

Comments Published at CoRL 2019

Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information

Dan Barnes, Rob Weston, Ingmar Posner

Comments Conference on Robot Learning (CoRL), 2019. Video summary: https://youtu.be/eG4Q-j3_6dk

Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks

Andreas Bühler, Niclas Vödisch, Mathias Bürki, Lukas Schaupp

Comments 8 pages, CoRL 2019 template used