CoRL

Parting with Misconceptions about Learning-based Vehicle Motion Planning

Daniel Dauner, Marcel Hallgarten, Andreas Geiger, Kashyap Chitta

Comments CoRL 2023

M2T2: Multi-Task Masked Transformer for Object-centric Pick and Place

Wentao Yuan, Adithyavairavan Murali, Arsalan Mousavian, Dieter Fox

Comments 12 pages, 8 figures, accepted by CoRL 2023

Learning to Design and Use Tools for Robotic Manipulation

Ziang Liu, Stephen Tian, Michelle Guo, C. Karen Liu, Jiajun Wu

Comments First two authors contributed equally. Accepted at CoRL 2023

Deception Game: Closing the Safety-Learning Loop in Interactive Robot Autonomy

Haimin Hu, Zixu Zhang, Kensuke Nakamura, Andrea Bajcsy, Jaime F. Fisac

Comments Conference on Robot Learning 2023

Task-Oriented Koopman-Based Control with Contrastive Encoder

Xubo Lyu, Hanyang Hu, Seth Siriya, Ye Pu, Mo Chen

Comments Accepted by the 7th Annual Conference on Robot Learning (CoRL), 2023 (oral spotlight)

Surrogate Assisted Generation of Human-Robot Interaction Scenarios

Varun Bhatt, Heramb Nemlekar, Matthew C. Fontaine, Bryon Tjanaka, Hejia Zhang, Ya-Chuan Hsu, Stefanos Nikolaidis

Comments 27 pages; 12 figures; 3 tables; Accepted for oral presentation at CoRL 2023

Learning Robot Manipulation from Cross-Morphology Demonstration

Gautam Salhotra, I-Chun Arthur Liu, Gaurav Sukhatme

Comments Accepted to the Conference on Robot Learning (CoRL) 2023

Stabilize to Act: Learning to Coordinate for Bimanual Manipulation

Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh

Comments Conference on Robot Learning, 2023

Katakomba: Tools and Benchmarks for Data-Driven NetHack

Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

Comments Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks. Source code at https://github.com/corl-team/katakomba

CORL: Research-oriented Deep Offline Reinforcement Learning Library

Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov

Comments Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks. Source code at https://github.com/corl-team/CORL

MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Ajay Mandlekar, Soroush Nasiriany, Bowen Wen, Iretiayo Akinola, Yashraj Narang, Linxi Fan, Yuke Zhu, Dieter Fox

Comments Conference on Robot Learning (CoRL) 2023

Large Language Models as General Pattern Machines

Suvir Mirchandani, Fei Xia, Pete Florence, Brian Ichter, Danny Driess, Montserrat Gonzalez Arenas, Kanishka Rao, Dorsa Sadigh, Andy Zeng

Comments 21 pages, 25 figures. To appear at Conference on Robot Learning (CoRL) 2023

Tuning Legged Locomotion Controllers via Safe Bayesian Optimization

Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros

Comments This paper has been accepted to the 2023 Conference on Robot Learning (CoRL 2023.) The first two authors contributed equally. The supplementary video is available at https://youtu.be/zDBouUgegrU and the code implementation is available at https://github.com/lasgroup/gosafeopt

Open-World Object Manipulation using Pre-trained Vision-Language Models

Austin Stone, Ted Xiao, Yao Lu, Keerthana Gopalakrishnan, Kuang-Huei Lee, Quan Vuong, Paul Wohlhart, Sean Kirmani, Brianna Zitkovich, Fei Xia, Chelsea Finn, Karol Hausman

Comments Accepted at the 7th Conference on Robot Learning (CoRL 2023)

Finetuning Offline World Models in the Real World

Yunhai Feng, Nicklas Hansen, Ziyan Xiong, Chandramouli Rajagopalan, Xiaolong Wang

Comments CoRL 2023 Oral; Project website: https://yunhaifeng.com/FOWM

Human-in-the-Loop Task and Motion Planning for Imitation Learning

Ajay Mandlekar, Caelan Garrett, Danfei Xu, Dieter Fox

Comments Conference on Robot Learning (CoRL) 2023

ViNT: A Foundation Model for Visual Navigation

Dhruv Shah, Ajay Sridhar, Nitish Dashora, Kyle Stachowicz, Kevin Black, Noriaki Hirose, Sergey Levine

Comments Accepted for oral presentation at CoRL 2023

Learning Generalizable Manipulation Policies with Object-Centric 3D Representations

Yifeng Zhu, Zhenyu Jiang, Peter Stone, Yuke Zhu

Comments Accepted at the 7th Annual Conference on Robot Learning (CoRL), 2023 in Atlanta, US

Learning Reward for Physical Skills using Large Language Model

Yuwei Zeng, Yiqing Xu

Comments CoRL 2023, LangRob workshop

STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience

Haresh Karnan, Elvin Yang, Daniel Farkash, Garrett Warnell, Joydeep Biswas, Peter Stone

Comments Project website: https://hareshkarnan.github.io/sterling/

Journal ref Conference on Robot Learning (CoRL 2023)

IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors

Gaurav Datta, Ryan Hoque, Anrui Gu, Eugen Solowjow, Ken Goldberg

Comments CoRL 2023

Fine-Tuning Generative Models as an Inference Method for Robotic Tasks

Orr Krupnik, Elisei Shafer, Tom Jurgenson, Aviv Tamar

Comments 7th Conference on Robot Learning, 2023. Project website at https://www.orrkrup.com/mace

CAT: Closed-loop Adversarial Training for Safe End-to-End Driving

Linrui Zhang, Zhenghao Peng, Quanyi Li, Bolei Zhou

Comments 7th Conference on Robot Learning (CoRL 2023)

Few-Shot In-Context Imitation Learning via Implicit Graph Alignment

Vitalis Vosylius, Edward Johns

Comments Published at CoRL 2023. Videos are available on our project webpage at https://www.robot-learning.uk/implicit-graph-alignment

One-Shot Imitation Learning: A Pose Estimation Perspective

Pietro Vitiello, Kamil Dreczkowski, Edward Johns

Comments Published at the 7th Conference on Robot Learning (CoRL 2023). For more details please visit https://www.robot-learning.uk/pose-estimation-perspective

Simultaneous Learning of Contact and Continuous Dynamics

Bibit Bianchini, Mathew Halm, Michael Posa

Comments 13 pages, 5 figures. Accepted to Conference on Robot Learning (CoRL) 2023. Project webpage with code, datasets, media, and OpenReview link at https://sites.google.com/view/continuous-contact-nets/home

Grounding Complex Natural Language Commands for Temporal Tasks in Unseen Environments

Jason Xinyu Liu, Ziyi Yang, Ifrah Idrees, Sam Liang, Benjamin Schornstein, Stefanie Tellex, Ankit Shah

Comments Conference on Robot Learning 2023

Stealthy Terrain-Aware Multi-Agent Active Search

Nikhil Angad Bakshi, Jeff Schneider

Comments 15 pages, 28 figures, for demo video see: https://youtu.be/Fs1lv4y6Nq8 , accepted for presentation in Conference on Robot Learning 2023, Atlanta, USA

Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance

Jesse Zhang, Jiahui Zhang, Karl Pertsch, Ziyi Liu, Xiang Ren, Minsuk Chang, Shao-Hua Sun, Joseph J. Lim

Comments CoRL 2023 (Oral); 24 pages, 11 figures

REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction

Zeyi Liu, Arpit Bahety, Shuran Song

Comments Conference on Robot Learning (CoRL) 2023; Project website: https://robot-reflect.github.io/