CoRL 2020

165 papers

STReSSD: Sim-To-Real from Sound for Stochastic Dynamics

Carolyn Matl, Yashraj Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos

Learning Dexterous Manipulation from Suboptimal Experts

Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Dan Zheng, Alexandre Galashov

Planning Paths Through Unknown Space by Imagining What Lies Therein

Yutao Han, Jacopo Banfi, Mark Campbell

TNT: Target-driven Trajectory Prediction

Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Ben Sapp

Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion

Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar

MuGNet: Multi-Resolution Graph Neural Network for Segmenting Large-Scale Pointclouds

Liuyue Xie, Tomotake Furuhata, Kenji Shimada

Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting Pedestrians

Bruno Ferreira de Brito, Hai Zhu, Wei Pan, Javier Alonso-Mora

Relational Learning for Skill Preconditions

Mohit Sharma, Oliver Kroemer

Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation

Mohit Sharma, Jacky Liang, Jialiang Zhao, Alex Lagrassa, Oliver Kroemer

Safe Policy Learning for Continuous Control

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar Duenez-Guzman, Mohammad Ghavamzadeh

Untangling Dense Knots by Learning Task-Relevant Keypoints

Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna

Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning

Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren

Assisted Perception: Optimizing Observations to Communicate State

Siddharth Reddy, Sergey Levine, Anca Dragan

Transporter Networks: Rearranging the Visual World for Robotic Manipulation

Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien

Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous

Rose Wang, J. Chase Kew, Dennis Lee, Tsang-Wei Lee, Tingnan Zhang

Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning

Lucas Manuelli, Yunzhu Li, Pete Florence, Russ Tedrake

Interactive Imitation Learning in State-Space

Snehal Jauhri, Carlos Celemin, Jens Kober

Sim-to-Real Transfer for Vision-and-Language Navigation

Peter Anderson, Ayush Shrivastava, Joanne Truong, Arjun Majumdar, Devi Parikh

Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions

Sarah Dean, Andrew Taylor, Ryan Cosner, Benjamin Recht, Aaron Ames

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

Kai Ploeger, Michael Lutter, Jan Peters

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection

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

The EMPATHIC Framework for Task Learning from Implicit Human Feedback

Yuchen Cui, Qiping Zhang, Brad Knox, Alessandro Allievi, Peter Stone

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments

Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger

Learning Latent Representations to Influence Multi-Agent Interaction

Annie Xie, Dylan Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

Learning Predictive Representations for Deformable Objects Using Contrastive Estimation

Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto

Iterative Semi-parametric Dynamics Model Learning For Autonomous Racing

Ignat Georgiev, Christoforos Chatzikomis, Timo Voelkl, Joshua Smith, Michael Mistry

f-IRL: Inverse Reinforcement Learning via State Marginal Matching

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

Learning hierarchical relationships for object-goal navigation

Anwesan Pal, Yiding Qiu, Henrik Christensen

Auxiliary Tasks Speed Up Learning Point Goal Navigation

Joel Ye, Dhruv Batra, Erik Wijmans, Abhishek Das

PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards

Prasoon Goyal, Scott Niekum, Raymond Mooney

Modeling Long-horizon Tasks as Sequential Interaction Landscapes

Soeren Pirk, Karol Hausman, Alexander Toshev, Mohi Khansari

Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

Yu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox

S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency

Mel Vecerik, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute

SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation

Xingyu Lin, Yufei Wang, Jake Olkin, David Held

Recovering and Simulating Pedestrians in the Wild

Ze Yang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma

One Thousand and One Hours: Self-driving Motion Prediction Dataset

John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen

Attention-Privileged Reinforcement Learning

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

Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects

Michael Danielczuk, Ashwin Balakrishna, Daniel Brown, Ken Goldberg

CLOUD: Contrastive Learning of Unsupervised Dynamics

Jianren Wang, Yujie Lu, Hang Zhao

Learning Obstacle Representations for Neural Motion Planning

Robin STRUDEL, Ricardo Garcia Pinel, Justin Carpentier, Jean-Paul Laumond, Ivan Laptev

Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn

PLOP: Probabilistic Polynomial Objects trajectory Prediction for autonomous driving

Thibault Buhet, Emilie Wirbel, Andrei Bursuc, Xavier Perrotton

Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents

Samyak Datta, Oleksandr Maksymets, Judy Hoffman, Stefan Lee, Dhruv Batra

Learning Object Manipulation Skills via Approximate State Estimation from Real Videos

Vladimír Petrík, Makarand Tapaswi, Ivan Laptev, Josef Sivic

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

Tai WANG, Xinge ZHU, Dahua Lin

SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving

Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu

Task-Relevant Adversarial Imitation Learning

Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden

Action-based Representation Learning for Autonomous Driving

Yi Xiao, Felipe Codevilla, Christopher Pal, Antonio Lopez

GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection

Kuang-Yu Jeng, Yueh-Cheng Liu, Zhe Yu Liu, Jen-Wei Wang, Ya-Liang Chang

Positive-Unlabeled Reward Learning

Danfei Xu, Misha Denil

Accelerating Reinforcement Learning with Learned Skill Priors

Karl Pertsch, Youngwoon Lee, Joseph Lim

Fit2Form: 3D Generative Model for Robot Gripper Form Design

Huy Ha, Shubham Agrawal, Shuran Song

SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning

Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck

CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow Estimation

Hengli Wang, Rui Fan, Ming Liu

Learning 3D Dynamic Scene Representations for Robot Manipulation

Zhenjia Xu, Zhanpeng He, Jiajun Wu, Shuran Song

SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks

Yan Xu, Zhaoyang Huang, Kwan-Yee Lin, Xinge ZHU, Jianping Shi

Learning a Decentralized Multi-Arm Motion Planner

Huy Ha, Jingxi Xu, Shuran Song

From pixels to legs: Hierarchical learning of quadruped locomotion

Deepali Jain, Ken Caluwaerts, Atil Iscen

Augmenting GAIL with BC for sample efficient imitation learning

Rohit Jena, Changliu Liu, Katia Sycara

CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs

Rohan Chitnis, Tom Silver, Beomjoon Kim, Leslie Kaelbling, Tomás Lozano-Pérez

DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning

Chiho Choi, Srikanth Malla, Abhishek Patil, Joon Hee Choi

LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion

Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber

Neuro-Symbolic Program Search for Autonomous Driving Decision Module Design

Jiankai Sun, Hao Sun, Tian Han, Bolei Zhou

Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting

Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart

Learning a Decision Module by Imitating Driver’s Control Behaviors

Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma, Chunxiao Liu