CoRL

PlanT: Explainable Planning Transformers via Object-Level Representations

Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, Andreas Geiger

Comments CoRL 2022. Project Page: https://www.katrinrenz.de/plant/

MidasTouch: Monte-Carlo inference over distributions across sliding touch

Sudharshan Suresh, Zilin Si, Stuart Anderson, Michael Kaess, Mustafa Mukadam

Comments Accepted at CoRL 2022 (Oral). Project website: https://suddhu.github.io/midastouch-tactile/

Learning Multi-Objective Curricula for Robotic Policy Learning

Jikun Kang, Miao Liu, Abhinav Gupta, Chris Pal, Xue Liu, Jie Fu

Comments CoRL 2022; Reinforcement Learning; Meta-Reinforcement Learning; Hyper-network

Motion Policy Networks

Adam Fishman, Adithyavairan Murali, Clemens Eppner, Bryan Peele, Byron Boots, Dieter Fox

Comments To be published in the Conference on Robot Learning (CoRL) 2022. 10 pages with 4 figures. Appendix has 10 pages and 1 figure

Hypernetworks in Meta-Reinforcement Learning

Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson

Comments Published at CoRL 2022

Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion

Zipeng Fu, Xuxin Cheng, Deepak Pathak

Comments CoRL 2022 (Oral). Project website at https://maniploco.github.io

Deep Black-Box Reinforcement Learning with Movement Primitives

Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann

Comments Accepted at CoRL 2022

On-Robot Learning With Equivariant Models

Dian Wang, Mingxi Jia, Xupeng Zhu, Robin Walters, Robert Platt

Comments Published at CoRL 2022

BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment

Zeyi Liu, Zhenjia Xu, Shuran Song

Comments CoRL 2022 camera-ready; Website: https://busybot.cs.columbia.edu/

Eliciting Compatible Demonstrations for Multi-Human Imitation Learning

Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh

Comments To appear at the 6th Annual Conference on Robot Learning (CoRL) 2022

Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds

Minghua Liu, Xuanlin Li, Zhan Ling, Yangyan Li, Hao Su

Comments Conference on Robot Learning (CoRL) 2022; Project Website: https://colin97.github.io/FrameMining/

Learning Neuro-Symbolic Skills for Bilevel Planning

Tom Silver, Ashay Athalye, Joshua B. Tenenbaum, Tomas Lozano-Perez, Leslie Pack Kaelbling

Comments CoRL 2022

In-Hand Gravitational Pivoting Using Tactile Sensing

Jason Toskov, Rhys Newbury, Mustafa Mukadam, Dana Kulić, Akansel Cosgun

Comments Accepted as poster presentation to Conference on Robot Learning (CoRL) 2022

In-Hand Object Rotation via Rapid Motor Adaptation

Haozhi Qi, Ashish Kumar, Roberto Calandra, Yi Ma, Jitendra Malik

Comments CoRL 2022. Code and Website: https://haozhi.io/hora

Learning the Dynamics of Compliant Tool-Environment Interaction for Visuo-Tactile Contact Servoing

Mark Van der Merwe, Dmitry Berenson, Nima Fazeli

Comments 6th Conference on Robotic Learning (CoRL 2022), Auckland, New Zealand. 8 pages + references + appendix

Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes

Joe Watson, Jan Peters

Comments 43 pages, 37 figures. Conference on Robot Learning 2022

Real-World Robot Learning with Masked Visual Pre-training

Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, Trevor Darrell

Comments CoRL 2022; Project page: https://tetexiao.com/projects/real-mvp

Visuo-Tactile Transformers for Manipulation

Yizhou Chen, Andrea Sipos, Mark Van der Merwe, Nima Fazeli

Comments Accepted to CoRL 2022

Manipulation via Membranes: High-Resolution and Highly Deformable Tactile Sensing and Control

Miquel Oller, Mireia Planas, Dmitry Berenson, Nima Fazeli

Comments 6th Conference on Robotic Learning (CoRL 2022), Auckland, New Zealand. 8 pages + references + appendix

CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers

Runsheng Xu, Zhengzhong Tu, Hao Xiang, Wei Shao, Bolei Zhou, Jiaqi Ma

Comments CoRL 2022; code: https://github.com/DerrickXuNu/CoBEVT

SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation

Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Yongming Rao, Guan Huang, Jiwen Lu, Jie Zhou

Comments Accepted to CoRL 2022. Project page: https://surrounddepth.ivg-research.xyz Code: https://github.com/weiyithu/SurroundDepth

Latent Plans for Task-Agnostic Offline Reinforcement Learning

Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard

Comments CoRL 2022. Project website: http://tacorl.cs.uni-freiburg.de/

One-Shot Transfer of Affordance Regions? AffCorrs!

Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas

Comments Published in Conference on Robot Learning, 2022 For code and dataset, refer to https://sites.google.com/view/affcorrs

Smooth Exploration for Robotic Reinforcement Learning

Antonin Raffin, Jens Kober, Freek Stulp

Comments Code: https://github.com/DLR-RM/stable-baselines3/ Training scripts: https://github.com/DLR-RM/rl-baselines3-zoo/

Journal ref Proceedings of the 5th Conference on Robot Learning, PMLR 164:1634-1644, 2022

Volumetric-based Contact Point Detection for 7-DoF Grasping

Junhao Cai, Jingcheng Su, Zida Zhou, Hui Cheng, Qifeng Chen, Michael Y Wang

Comments Accepted to Conference on Robot Learning (CoRL) 2022. Supplementary materials: https://openreview.net/forum?id=SrSCqW4dq9

SORNet: Spatial Object-Centric Representations for Sequential Manipulation

Wentao Yuan, Chris Paxton, Karthik Desingh, Dieter Fox

Comments CoRL 2021 Best Systems Paper Finalist; Code and data available at https://github.com/wentaoyuan/sornet

SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

Comments Accepted to CoRL-2022

Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Nikita Rudin, David Hoeller, Philipp Reist, Marco Hutter

Comments CoRL 2021 Project website: : https://leggedrobotics.github.io/legged_gym/ Video: https://youtu.be/8sO7VS3q8d0

TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs

Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti

Comments Video: https://www.youtube.com/watch?v=mM4v5hP4LdA&ab_channel=KrishnaMurthy . Project page: https://taskography.github.io/ . 18 pages, 7 figures. In proceedings of Conference on Robot Learning (CoRL) 2021. The first two authors contributed equally

Journal ref PMLR 164 (2022) 46-58

Learning Model Preconditions for Planning with Multiple Models

Alex LaGrassa, Oliver Kroemer

Comments Presented at Conference on Robot Learning (CoRL 2021). Revised for clarity

Journal ref Proceedings of the 5th Conference on Robot Learning, PMLR 164 (2022) 491-500