Conference on Robot Learning

CoRL

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Fields of research

Artificial Intelligence · Machine Learning · Computer Vision and Multimedia Computation

Papers indexed

1,225

2017–2024

Best Artificial Intelligence conferences Best Machine Learning conferences Best Computer Vision conferences

Papers per year

2017264 peak2024

Most published authors

CoRL papers

1,225 records sourced from DBLP. Search titles, filter by year, sort by recency.

Year	Title	Authors
2020	Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs.	Marcus Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou
2020	Learning to Improve Multi-Robot Hallway Navigation.	Jin Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, Peter Stone
2020	Learning hierarchical relationships for object-goal navigation.	Anwesan Pal, Yiding Qiu, Henrik I. Christensen
2020	Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach.	Kartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman Khetan, Aditya Varma, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya
2020	Deep Reactive Planning in Dynamic Environments.	Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski
2020	Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial Insertion.	Boshen Niu, Chenxi Wang, Changliu Liu
2020	f-IRL: Inverse Reinforcement Learning via State Marginal Matching.	Tianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Ben Eysenbach
2020	Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation Planning.	Son Nguyen, Ozgur S. Oguz, Valentin N. Hartmann, Marc Toussaint
2020	Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability.	Hai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt
2020	EXI-Net: EXplicitly/Implicitly Conditioned Network for Multiple Environment Sim-to-Real Transfer.	Takayuki Murooka, Masashi Hamaya, Felix von Drigalski, Kazutoshi Tanaka, Yoshihisa Ijiri
2020	Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping.	Adithyavairavan Murali, Weiyu Liu, Kenneth Marino, Sonia Chernova, Abhinav Gupta
2020	A User's Guide to Calibrating Robotic Simulators.	Bhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos
2020	STReSSD: Sim-To-Real from Sound for Stochastic Dynamics.	Carolyn Matl, Yashraj Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos
2020	Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning.	Lucas Manuelli, Yunzhu Li, Peter R. Florence, Russ Tedrake
2020	SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation.	Xingyu Lin, Yufei Wang, Jake Olkin, David Held
2020	Learning Hybrid Control Barrier Functions from Data.	Lars Lindemann, Haimin Hu, Alexander Robey, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, Nikolai Matni
2020	Unsupervised Monocular Depth Learning in Dynamic Scenes.	Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova
2020	Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling.	Thomas Lew, Marco Pavone
2020	Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience.	Robert Lee, Daniel Ward, Vibhavari Dasagi, Akansel Cosgun, Juxi Leitner, Peter Corke
2020	Stein Variational Model Predictive Control.	Alexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman
2020	Towards Autonomous Eye Surgery by Combining Deep Imitation Learning with Optimal Control.	Ji Woong Kim, Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov
2020	DeepMPCVS: Deep Model Predictive Control for Visual Servoing.	Pushkal Katara, Y. V. S. Harish, Harit Pandya, Abhinav Gupta, AadilMehdi J. Sanchawala, Gourav Kumar, Brojeshwar Bhowmick, K. Madhava Krishna
2020	Unsupervised Metric Relocalization Using Transform Consistency Loss.	Mike Kasper, Fernando Nobre, Christoffer Heckman, Nima Keivan
2020	Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning.	Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman
2020	Asynchronous Deep Model Reference Adaptive Control.	Girish Joshi, Jasvir Virdi, Girish Chowdhary

901–925 of 1,225← Previous Next →

Comparable venues

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