CoRL 2022

197 papers

QuaDUE-CCM: Interpretable Distributional Reinforcement Learning using Uncertain Contraction Metrics for Precise Quadrotor Trajectory Tracking

Yanran Wang, James O’Keeffe, Qiuchen Qian, David Boyle

CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion

Tobias Fischer, Yung-Hsu Yang, Suryansh Kumar, Min Sun, Fisher Yu

In-Hand Gravitational Pivoting Using Tactile Sensing

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

Data-Efficient Model Learning for Control with Jacobian-Regularized Dynamic-Mode Decomposition

Brian Edward Jackson, Jeong Hun Lee, Kevin Tracy, Zachary Manchester

Skill-based Model-based Reinforcement Learning

Lucy Xiaoyang Shi, Youngwoon Lee, Joseph J. Lim, Joseph J Lim

Online Dynamics Learning for Predictive Control with an Application to Aerial Robots

Tom Z. Jiahao, Kong Yao Chee, M. Ani Hsieh

INQUIRE: INteractive Querying for User-aware Informative REasoning

Tesca Fitzgerald, Pallavi Koppol, Patrick Callaghan, Russell Quinlan Jun Hei Wong, Reid Simmons

DayDreamer: World Models for Physical Robot Learning

Philipp Wu, Alejandro Escontrela, Danijar Hafner, Pieter Abbeel, Ken Goldberg

TRITON: Neural Neural Textures for Better Sim2Real

Ryan D. Burgert, Jinghuan Shang, Xiang Li, Michael S. Ryoo

Learning Semantics-Aware Locomotion Skills from Human Demonstration

Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan

Learning and Retrieval from Prior Data for Skill-based Imitation Learning

Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu

DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone

Contrastive Decision Transformers

Sachin G. Konan, Esmaeil Seraj, Matthew Gombolay

Safe Robot Learning in Assistive Devices through Neural Network Repair

Keyvan Majd, Geoffrey Mitchell Clark, Tanmay Khandait, Siyu Zhou, Sriram Sankaranarayanan

ROAD: Learning an Implicit Recursive Octree Auto-Decoder to Efficiently Encode 3D Shapes

Sergey Zakharov, Rares Andrei Ambrus, Katherine Liu, Adrien Gaidon

Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Tyler Westenbroek, Fernando Castaneda, Ayush Agrawal, Shankar Sastry, Koushil Sreenath

Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning

Yoonchang Sung, Zizhao Wang, Peter Stone

Learning Representations that Enable Generalization in Assistive Tasks

Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Aditi Raghunathan, Anca Dragan

Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics

Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, Niko Suenderhauf

Fast Lifelong Adaptive Inverse Reinforcement Learning from Demonstrations

Letian Chen, Sravan Jayanthi, Rohan R Paleja, Daniel Martin, Viacheslav Zakharov

USHER: Unbiased Sampling for Hindsight Experience Replay

Liam Schramm, Yunfu Deng, Edgar Granados, Abdeslam Boularias

Multi-Robot Scene Completion: Towards Task-Agnostic Collaborative Perception

Yiming Li, Juexiao Zhang, Dekun Ma, Yue Wang, Chen Feng

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

Mark Van der Merwe, Dmitry Berenson, Nima Fazeli

Offline Reinforcement Learning at Multiple Frequencies

Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman

Visuo-Tactile Transformers for Manipulation

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

Few-Shot Preference Learning for Human-in-the-Loop RL

Donald Joseph Hejna III, Dorsa Sadigh

Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes

Haoxiang Ma, Di Huang

When the Sun Goes Down: Repairing Photometric Losses for All-Day Depth Estimation

Madhu Vankadari, Stuart Golodetz, Sourav Garg, Sangyun Shin, Andrew Markham

Eliciting Compatible Demonstrations for Multi-Human Imitation Learning

Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh

Safe Control Under Input Limits with Neural Control Barrier Functions

Simin Liu, Changliu Liu, John Dolan

Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles

Alec Farid, Sushant Veer, Boris Ivanovic, Karen Leung, Marco Pavone

Verified Path Following Using Neural Control Lyapunov Functions

Alec Reed, Guillaume O Berger, Sriram Sankaranarayanan, Chris Heckman

Learning Diverse and Physically Feasible Dexterous Grasps with Generative Model and Bilevel Optimization

Albert Wu, Michelle Guo, Karen Liu

CAtNIPP: Context-Aware Attention-based Network for Informative Path Planning

Yuhong Cao, Yizhuo Wang, Apoorva Vashisth, Haolin Fan, Guillaume Adrien Sartoretti

MIRA: Mental Imagery for Robotic Affordances

Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du

Towards Long-Tailed 3D Detection

Neehar Peri, Achal Dave, Deva Ramanan, Shu Kong

GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots

Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy

Learning Road Scene-level Representations via Semantic Region Prediction

Zihao Xiao, Alan Yuille, Yiting Chen, Yi-Ting Chen

Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data

John So, Amber Xie, Sunggoo Jung, Jeffrey Edlund, Rohan Thakker

Real-Time Generation of Time-Optimal Quadrotor Trajectories with Semi-Supervised Seq2Seq Learning

Gilhyun Ryou, Ezra Tal, Sertac Karaman

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

Miquel Oller, Mireia Planas i Lisbona, Dmitry Berenson, Nima Fazeli

Latent Plans for Task-Agnostic Offline Reinforcement Learning

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

Concept Learning for Interpretable Multi-Agent Reinforcement Learning

Renos Zabounidis, Joseph Campbell, Simon Stepputtis, Dana Hughes, Katia P. Sycara

Detecting Incorrect Visual Demonstrations for Improved Policy Learning

Mostafa Hussein, Momotaz Begum

VIRDO++: Real-World, Visuo-tactile Dynamics and Perception of Deformable Objects

Youngsun Wi, Andy Zeng, Pete Florence, Nima Fazeli

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

Prarthana Bhattacharyya, Chengjie Huang, Krzysztof Czarnecki

TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation

Chuer Pan, Brian Okorn, Harry Zhang, Ben Eisner, David Held

Inner Monologue: Embodied Reasoning through Planning with Language Models

Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang

Learning Multi-Object Dynamics with Compositional Neural Radiance Fields

Danny Driess, Zhiao Huang, Yunzhu Li, Russ Tedrake, Marc Toussaint

Embodied Concept Learner: Self-supervised Learning of Concepts and Mapping through Instruction Following

Mingyu Ding, Yan Xu, Zhenfang Chen, David Daniel Cox, Ping Luo

Learning Sampling Distributions for Model Predictive Control

Jacob Sacks, Byron Boots

In-Hand Object Rotation via Rapid Motor Adaptation

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

Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation

Xuesu Xiao, Tingnan Zhang, Krzysztof Marcin Choromanski, Tsang-Wei Edward Lee, Anthony Francis

PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale

Kuang-Huei Lee, Ted Xiao, Adrian Li, Paul Wohlhart, Ian Fischer

Modularity through Attention: Efficient Training and Transfer of Language-Conditioned Policies for Robot Manipulation

Yifan Zhou, Shubham Sonawani, Mariano Phielipp, Simon Stepputtis, Heni Amor

Leveraging Fully Observable Policies for Learning under Partial Observability

Hai Huu Nguyen, Andrea Baisero, Dian Wang, Christopher Amato, Robert Platt

LaRa: Latents and Rays for Multi-Camera Bird’s-Eye-View Semantic Segmentation

Florent Bartoccioni, Eloi Zablocki, Andrei Bursuc, Patrick Pérez, Matthieu Cord

Don’t Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning

Homer Rich Walke, Jonathan Heewon Yang, Albert Yu, Aviral Kumar, Jȩdrzej Orbik

Planning with Spatial-Temporal Abstraction from Point Clouds for Deformable Object Manipulation

Xingyu Lin, Carl Qi, Yunchu Zhang, Zhiao Huang, Katerina Fragkiadaki

HTRON: Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm

Kasun Weerakoon, Souradip Chakraborty, Nare Karapetyan, Adarsh Jagan Sathyamoorthy, Amrit Bedi

Touching a NeRF: Leveraging Neural Radiance Fields for Tactile Sensory Data Generation

Shaohong Zhong, Alessandro Albini, Oiwi Parker Jones, Perla Maiolino, Ingmar Posner

Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty

Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang

Visuotactile Affordances for Cloth Manipulation with Local Control

Neha Sunil, Shaoxiong Wang, Yu She, Edward Adelson, Alberto Rodriguez Garcia

Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation

Bugra Can Sefercik, Baris Akgun

Deep Projective Rotation Estimation through Relative Supervision

Brian Okorn, Chuer Pan, Martial Hebert, David Held

Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming

Krishna Murthy Jatavallabhula, Miles Macklin, Dieter Fox, Animesh Garg, Fabio Ramos

Do we use the Right Measure? Challenges in Evaluating Reward Learning Algorithms

Nils Wilde, Javier Alonso-Mora

Adapting Neural Models with Sequential Monte Carlo Dropout

Pamela Carreno, Dana Kulic, Michael Burke

Leveraging Language for Accelerated Learning of Tool Manipulation

Allen Z. Ren, Bharat Govil, Tsung-Yen Yang, Karthik R Narasimhan, Anirudha Majumdar

SE(3)-Equivariant Point Cloud-Based Place Recognition

Chien Erh Lin, Jingwei Song, Ray Zhang, Minghan Zhu, Maani Ghaffari

Learning Bimanual Scooping Policies for Food Acquisition

Jennifer Grannen, Yilin Wu, Suneel Belkhale, Dorsa Sadigh

Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates

Souradeep Dutta, Kaustubh Sridhar, Osbert Bastani, Edgar Dobriban, James Weimer

Efficient Tactile Simulation with Differentiability for Robotic Manipulation

Jie Xu, Sangwoon Kim, Tao Chen, Alberto Rodriguez Garcia, Pulkit Agrawal

Hypernetworks in Meta-Reinforcement Learning

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

Online Inverse Reinforcement Learning with Learned Observation Model

Saurabh Arora, Prashant Doshi, Bikramjit Banerjee

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving

Wenjie Luo, Cheol Park, Andre Cornman, Benjamin Sapp, Dragomir Anguelov

ARC - Actor Residual Critic for Adversarial Imitation Learning

Ankur Deka, Changliu Liu, Katia P. Sycara

You Only Look at One: Category-Level Object Representations for Pose Estimation From a Single Example

Walter Goodwin, Ioannis Havoutis, Ingmar Posner

PLATO: Predicting Latent Affordances Through Object-Centric Play

Suneel Belkhale, Dorsa Sadigh

ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction

Christopher Mower, Theodoros Stouraitis, João Moura, Christian Rauch, Lei Yan

Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping

Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Alessandro Lazaric, Karteek Alahari

Generative Category-Level Shape and Pose Estimation with Semantic Primitives

Guanglin Li, Yifeng Li, Zhichao Ye, Qihang Zhang, Tao Kong

Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors

Niklas Freymuth, Nicolas Schreiber, Aleksandar Taranovic, Philipp Becker, Gerhard Neumann

See, Hear, and Feel: Smart Sensory Fusion for Robotic Manipulation

Hao Li, Yizhi Zhang, Junzhe Zhu, Shaoxiong Wang, Michelle A Lee

Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration

Mandy Xie, Ankur Handa, Stephen Tyree, Dieter Fox, Harish Ravichandar

On-Robot Learning With Equivariant Models

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

Masked World Models for Visual Control

Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James

GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automation

Jiaheng Hu, Julian Whitman, Howie Choset

Robustness Certification of Visual Perception Models via Camera Motion Smoothing

Hanjiang Hu, ZUXIN LIU, Linyi Li, Jiacheng Zhu, Ding Zhao

Solving Complex Manipulation Tasks with Model-Assisted Model-Free Reinforcement Learning

Jianshu Hu, Paul Weng

Learning Interpretable BEV Based VIO without Deep Neural Networks

Zexi Chen, Haozhe Du, Xuecheng Xu, Rong Xiong, Yiyi Liao

Representation Learning for Object Detection from Unlabeled Point Cloud Sequences

Xiangru Huang, Yue Wang, Vitor Campagnolo Guizilini, Rares Andrei Ambrus, Adrien Gaidon

Discriminator-Guided Model-Based Offline Imitation Learning

Wenjia Zhang, Haoran Xu, Haoyi Niu, Peng CHENG, Ming Li

Deep Black-Box Reinforcement Learning with Movement Primitives

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

Learning Visualization Policies of Augmented Reality for Human-Robot Collaboration

Kishan Dhananjay Chandan, Jack Albertson, Shiqi Zhang

Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation

Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian

Learning Riemannian Stable Dynamical Systems via Diffeomorphisms

Jiechao Zhang, Hadi Beik Mohammadi, Leonel Rozo

VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors

Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu

Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments

Matthew Budd, Paul Duckworth, Nick Hawes, Bruno Lacerda

Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt