CoRL

CLASP: Constrained Latent Shape Projection for Refining Object Shape from Robot Contact

Brad Saund, Dmitry Berenson

Comments 16 pages, 10 figures, Accepted at the Conference on Robot Learning (CoRL) 2021

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

Benedikt Mersch, Xieyuanli Chen, Jens Behley, Cyrill Stachniss

Comments Accepted for CoRL 2021

Macro-Action-Based Deep Multi-Agent Reinforcement Learning

Yuchen Xiao, Joshua Hoffman, Christopher Amato

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

Influencing Towards Stable Multi-Agent Interactions

Woodrow Z. Wang, Andy Shih, Annie Xie, Dorsa Sadigh

Comments 15 pages, 5 figures, Published as an Oral at Conference on Robot Learning (CoRL) 2021

Dual-Arm Adversarial Robot Learning

Elie Aljalbout

Comments Accepted at CoRL 2021, Blue Sky Track

RoCUS: Robot Controller Understanding via Sampling

Yilun Zhou, Serena Booth, Nadia Figueroa, Julie Shah

Comments CoRL 2021. The project website is at https://yilunzhou.github.io/RoCUS/

DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries

Yue Wang, Vitor Guizilini, Tianyuan Zhang, Yilun Wang, Hang Zhao, Justin Solomon

Comments Accepted to CORL 2021

LENS: Localization enhanced by NeRF synthesis

Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle

Comments Accepted at CoRL 2021

Auditing Robot Learning for Safety and Compliance during Deployment

Homanga Bharadhwaj

Comments Blue Sky paper at the 5th Conference on Robot Learning (CoRL 2021)

STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation

Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan Ratliff, Dieter Fox, Fabio Ramos, Byron Boots

Comments Accepted for oral presentation at the Conference on Robot Learning (CoRL), 2021. Code available at: https://github.com/NVlabs/storm

Journal ref 5th Annual Conference on Robot Learning, 2021

Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions

Charles Dawson, Zengyi Qin, Sicun Gao, Chuchu Fan

Comments Accepted to the 5th Annual Conference on Robot Learning (CoRL 21)

You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL

Wonjoon Goo, Scott Niekum

Comments In proceedings of 5th Annual Conference on Robot Learning (CoRL) 2021

Learning Off-Policy with Online Planning

Harshit Sikchi, Wenxuan Zhou, David Held

Comments 30 pages, Conference of Robot Learning (CoRL) 2021

Fully Self-Supervised Class Awareness in Dense Object Descriptors

Denis Hadjivelichkov, Dimitrios Kanoulas

Comments CoRL 2021, Site: https://sites.google.com/view/multi-object-dense-descriptors

Learning Reward Functions from Scale Feedback

Nils Wilde, Erdem Bıyık, Dorsa Sadigh, Stephen L. Smith

Comments 16 pages, 15 figures, 3 tables. Published at Conference on Robot Learning (CoRL) 2021

Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects

Haoping Xu, Yi Ru Wang, Sagi Eppel, Alàn Aspuru-Guzik, Florian Shkurti, Animesh Garg

Comments Accepted for Oral at Conference on Robot Learning (CoRL) 2021; Haoping Xu and Yi Ru Wang contributed equally; 8 pages, 6 figures, 3 tables

Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients

Oliver Scheel, Luca Bergamini, Maciej Wołczyk, Błażej Osiński, Peter Ondruska

Comments CoRL 2021

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín

Comments CoRL 2021 (Oral)

CLIPort: What and Where Pathways for Robotic Manipulation

Mohit Shridhar, Lucas Manuelli, Dieter Fox

Comments CoRL 2021. Project Website: https://cliport.github.io/

A Workflow for Offline Model-Free Robotic Reinforcement Learning

Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine

Comments CoRL 2021. Project Website: https://sites.google.com/view/offline-rl-workflow. First two authors contributed equally

Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes

Jongseok Lee, Jianxiang Feng, Matthias Humt, Marcus G. Müller, Rudolph Triebel

Comments 12 pages, 6 figures and 1 table. Accepted at the 5th Conference on Robot Learning (CORL 2021), London, UK

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks

Albert Wilcox, Ashwin Balakrishna, Brijen Thananjeyan, Joseph E. Gonzalez, Ken Goldberg

Comments Conference on Robot Learning (CoRL) 2021. First two authors contributed equally

Journal ref Conference on Robot Learning (CoRL) 2021

ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning

Ryan Hoque, Ashwin Balakrishna, Ellen Novoseller, Albert Wilcox, Daniel S. Brown, Ken Goldberg

Comments CoRL 2021 Oral

Language Grounding with 3D Objects

Jesse Thomason, Mohit Shridhar, Yonatan Bisk, Chris Paxton, Luke Zettlemoyer

Comments Conference on Robot Learning (CoRL) 2021

SCAPE: Learning Stiffness Control from Augmented Position Control Experiences

Mincheol Kim, Scott Niekum, Ashish D. Deshpande

Comments Accepted at CoRL 2021

Learning Density Distribution of Reachable States for Autonomous Systems

Yue Meng, Dawei Sun, Zeng Qiu, Md Tawhid Bin Waez, Chuchu Fan

Comments Accepted at CoRL 2021

Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds

Lirui Wang, Yu Xiang, Wei Yang, Arsalan Mousavian, Dieter Fox

Journal ref The Conference on Robot Learning (CoRL 2021)

Tactile Image-to-Image Disentanglement of Contact Geometry from Motion-Induced Shear

Anupam K. Gupta, Laurence Aitchison, Nathan F. Lepora

Comments 15 pages, 6 figure, under review CORL 2021

Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning

Sean Gillen, Katie Byl

Comments Presented at CORL 2020

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Avnish Narayan, Hayden Shively, Adithya Bellathur, Karol Hausman, Chelsea Finn, Sergey Levine

Comments This is an update version of a manuscript that originally appeared at CoRL 2019. Videos are here: meta-world.github.io, open-sourced code are available at: https://github.com/rlworkgroup/metaworld, and the baselines can be found at https://github.com/rlworkgroup/garage