CoRL

Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps

Chengguang Xu, Christopher Amato, Lawson L. S. Wong

Comments 21 pages, Conference on Robot Learning 2020, Boston, MA

Flightmare: A Flexible Quadrotor Simulator

Yunlong Song, Selim Naji, Elia Kaufmann, Antonio Loquercio, Davide Scaramuzza

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

Learning a Decision Module by Imitating Driver's Control Behaviors

Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma, Chunxiao Liu, Jianping Shi, Dahua Lin, Bolei Zhou

Comments Proceedings of the Conference on Robot Learning (CoRL) 2020

DeepMPCVS: Deep Model Predictive Control for Visual Servoing

Pushkal Katara, Y V S Harish, Harit Pandya, Abhinav Gupta, Aadil Mehdi Sanchawala, Gourav Kumar, Brojeshwar Bhowmick, Madhava Krishna K

Comments Accepted at 4th Annual Conference on Robot Learning, CoRL 2020, Cambridge, MA, USA, November 16 - November 18, 2020

Journal ref 4th Annual Conference on Robot Learning, CoRL 2020, Cambridge, MA, USA, November 16 - November 18, 2020

Stein Variational Model Predictive Control

Alexander Lambert, Adam Fishman, Dieter Fox, Byron Boots, Fabio Ramos

Comments Accepted to Conference on Robot Learning (CoRL) 2020

Learning Obstacle Representations for Neural Motion Planning

Robin Strudel, Ricardo Garcia, Justin Carpentier, Jean-Paul Laumond, Ivan Laptev, Cordelia Schmid

Comments CoRL 2020. See the project webpage at https://www.di.ens.fr/willow/research/nmp_repr/

Learning a natural-language to LTL executable semantic parser for grounded robotics

Christopher Wang, Candace Ross, Yen-Ling Kuo, Boris Katz, Andrei Barbu

Comments 10 pages, 2 figures, Accepted in Conference on Robot Learning (CoRL) 2020

SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation

Xingyu Lin, Yufei Wang, Jake Olkin, David Held

Comments Conference on Robot Learning, 2020

Model Based Planning with Energy Based Models

Yilun Du, Toru Lin, Igor Mordatch

Comments CoRL 2019

Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

Yu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox

Comments CoRL 2020

Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space

Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Daniela Rus

Comments Wilko, Tim, and Igor contributed equally to this work; published in Conference on Robot Learning 2020

Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs

Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou

Journal ref Conference on Robot Learning 2020

Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning

Le Chen, Yunke Ao, Florian Tschopp, Andrei Cramariuc, Michel Breyer, Jen Jen Chung, Roland Siegwart, Cesar Cadena

Journal ref Proceedings of the 4th Conference on Robot Learning (CoRL) 2020

Learning from Demonstrations using Signal Temporal Logic

Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis

Comments Published at Conference on Robot Learning (CoRL) 2020

Multi-Resolution Graph Neural Network for Large-Scale Pointcloud Segmentation

Liuyue Xie, Tomotake Furuhata, Kenji Shimada

Journal ref Conference on Robot Learning, 2020, 184

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection

Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu

Comments CoRL 2020

IntentNet: Learning to Predict Intention from Raw Sensor Data

Sergio Casas, Wenjie Luo, Raquel Urtasun

Comments CoRL 2018

MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control

Boris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone

Comments 14 pages, 6 figures, 1 table. All code, models, and data can be found at https://github.com/StanfordASL/MATS . Conference on Robot Learning (CoRL) 2020

MELD: Meta-Reinforcement Learning from Images via Latent State Models

Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine

Comments Accepted to CoRL 2020. Supplementary material at https://sites.google.com/view/meld-lsm/home . 16 pages, 19 figures. V2: add funding acknowledgements, reduce file size

Attention-Privileged Reinforcement Learning

Sasha Salter, Dushyant Rao, Markus Wulfmeier, Raia Hadsell, Ingmar Posner

Comments Published at Conference on Robot Learning (CoRL) 2020

DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer

Ajay Kumar Tanwani

Comments 4th Conference on Robot Learning (CoRL), 2020 [plenary talk, Best System Paper Award Finalist]

Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter

Michel Breyer, Jen Jen Chung, Lionel Ott, Roland Siegwart, Juan Nieto

Comments Conference on Robot Learning (CoRL), 2020

f-IRL: Inverse Reinforcement Learning via State Marginal Matching

Tianwei Ni, Harshit Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Benjamin Eysenbach

Comments The first four authors have equal contribution (orders determined by dice rolling), and the last two authors have equal advising. The paper is accepted by Conference on Robot Learning (CoRL) 2020. Project videos and code link are available at https://sites.google.com/view/f-irl/home

HDNET: Exploiting HD Maps for 3D Object Detection

Bin Yang, Ming Liang, Raquel Urtasun

Comments Spotlight paper at 2nd Conference on Robot Learning (CoRL 2018)

Learning to Localize Using a LiDAR Intensity Map

Ioan Andrei Bârsan, Shenlong Wang, Andrei Pokrovsky, Raquel Urtasun

Comments 12 pages, 7 figures, 5 tables; Presented at the 2nd Conference on Robot Learning (CoRL), 2018

Journal ref Proceedings of The 2nd Conference on Robot Learning, PMLR 87:605-616, 2018

Multi-Modal Anomaly Detection for Unstructured and Uncertain Environments

Tianchen Ji, Sri Theja Vuppala, Girish Chowdhary, Katherine Driggs-Campbell

Comments Conference on Robot Learning (CoRL) 2020

Using Reinforcement Learning to Herd a Robotic Swarm to a Target Distribution

Zahi M. Kakish, Karthik Elamvazhuthi, Spring Berman

Comments Paper was submitted to Conference on Robot Learning 2019 and IEEE Robotics and Automation Letters 2020 Revised, updated, and submitted to DARS/SWARMS 2021

Learning 3D Dynamic Scene Representations for Robot Manipulation

Zhenjia Xu, Zhanpeng He, Jiajun Wu, Shuran Song

Comments CoRL 2020. The first two authors contributed equally to this paper. Project page: https://dsr-net.cs.columbia.edu/

Tactile Object Pose Estimation from the First Touch with Geometric Contact Rendering

Maria Bauza, Eric Valls, Bryan Lim, Theo Sechopoulos, Alberto Rodriguez

Comments CORL 2020, 5 figures + 2 in appendix Video: https://youtu.be/2ygtSJTmo08

The EMPATHIC Framework for Task Learning from Implicit Human Feedback

Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox

Comments Conference on Robot Learning 2020