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4th CoRL 2020: Virtual Event / Cambridge, MA, USA
- Jens Kober, Fabio Ramos, Claire J. Tomlin:
4th Conference on Robot Learning, CoRL 2020, 16-18 November 2020, Virtual Event / Cambridge, MA, USA. Proceedings of Machine Learning Research 155, PMLR 2020 - Junning Huang, Sirui Xie, Jiankai Sun, Gary Qiurui Ma
, Chunxiao Liu, Dahua Lin, Bolei Zhou:
Learning a Decision Module by Imitating Driver's Control Behaviors. 1-10 - Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart:
Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting. 11-20 - Jiankai Sun, Hao Sun, Tian Han, Bolei Zhou:
Neuro-Symbolic Program Search for Autonomous Driving Decision Module Design. 21-30 - Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sida Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun:
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion. 31-48 - Chiho Choi, Srikanth Malla, Abhishek Patil, Joon Hee Choi:
DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning. 49-63 - Rohan Chitnis, Tom Silver, Beomjoon Kim, Leslie Pack Kaelbling, Tomás Lozano-Pérez:
CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs. 64-79 - Rohit Jena, Changliu Liu, Katia P. Sycara:
Augmenting GAIL with BC for sample efficient imitation learning. 80-90 - Deepali Jain, Ken Caluwaerts, Atil Iscen:
From pixels to legs: Hierarchical learning of quadruped locomotion. 91-102 - Huy Ha, Jingxi Xu, Shuran Song:
Learning a Decentralized Multi-Arm Motion Planner. 103-114 - Yan Xu, Zhaoyang Huang, Kwan-Yee Lin, Xinge Zhu, Jianping Shi, Hujun Bao, Guofeng Zhang, Hongsheng Li:
SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks. 115-125 - Zhenjia Xu, Zhanpeng He, Jiajun Wu, Shuran Song:
Learning 3D Dynamic Scene Representations for Robot Manipulation. 126-142 - Hengli Wang, Rui Fan, Ming Liu:
CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow Estimation. 143-155 - Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto:
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning. 156-175 - Huy Ha, Shubham Agrawal, Shuran Song:
Fit2Form: 3D Generative Model for Robot Gripper Form Design. 176-187 - Karl Pertsch, Youngwoon Lee, Joseph J. Lim:
Accelerating Reinforcement Learning with Learned Skill Priors. 188-204 - Danfei Xu, Misha Denil:
Positive-Unlabeled Reward Learning. 205-219 - Kuang-Yu Jeng, Yueh-Cheng Liu, Zhe Yu Liu, Jen-Wei Wang, Ya-Liang Chang, Hung-Ting Su, Winston H. Hsu:
GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection. 220-231 - Yi Xiao, Felipe Codevilla, Christopher J. Pal, Antonio M. López:
Action-based Representation Learning for Autonomous Driving. 232-246 - Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang:
Task-Relevant Adversarial Imitation Learning. 247-263 - Ming Zhou
SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving. 264-285 - Tai Wang, Xinge Zhu, Dahua Lin:
Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds. 286-295 - Vladimír Petrík, Makarand Tapaswi, Ivan Laptev, Josef Sivic:
Learning Object Manipulation Skills via Approximate State Estimation from Real Videos. 296-312 - Samyak Datta, Oleksandr Maksymets, Judy Hoffman
Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents. 313-328 - Thibault Buhet, Émilie Wirbel, Andrei Bursuc, Xavier Perrotton:
PLOP: Probabilistic Polynomial Objects trajectory Prediction for autonomous driving. 329-338 - Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn:
Reinforcement Learning with Videos: Combining Offline Observations with Interaction. 339-354 - Robin Strudel, Ricardo Garcia, Justin Carpentier, Jean-Paul Laumond, Ivan Laptev, Cordelia Schmid:
Learning Obstacle Representations for Neural Motion Planning. 355-364 - Jianren Wang, Yujie Lu, Hang Zhao:
CLOUD: Contrastive Learning of Unsupervised Dynamics. 365-376 - Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Ken Goldberg:
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects. 377-393 - Sasha Salter, Dushyant Rao, Markus Wulfmeier, Raia Hadsell, Ingmar Posner:
Attention-Privileged Reinforcement Learning. 394-408 - John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska:
One Thousand and One Hours: Self-driving Motion Prediction Dataset. 409-418 - Ze Yang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
Recovering and Simulating Pedestrians in the Wild. 419-431 - Xingyu Lin, Yufei Wang, Jake Olkin, David Held:
SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation. 432-448 - Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz:
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. 449-460 - Yu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox:
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation. 461-470 - Sören Pirk, Karol Hausman, Alexander Toshev, Mohi Khansari:
Modeling Long-horizon Tasks as Sequential Interaction Landscapes. 471-484 - Prasoon Goyal, Scott Niekum, Raymond J. Mooney:
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. 485-497 - Joel Ye, Dhruv Batra, Erik Wijmans, Abhishek Das:
Auxiliary Tasks Speed Up Learning Point Goal Navigation. 498-516 - Anwesan Pal, Yiding Qiu, Henrik I. Christensen:
Learning hierarchical relationships for object-goal navigation. 517-528 - Tianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Ben Eysenbach:
f-IRL: Inverse Reinforcement Learning via State Marginal Matching. 529-551 - Ignat Georgiev, Christoforos Chatzikomis, Timo Völkl, Joshua Smith, Michael N. Mistry:
Iterative Semi-parametric Dynamics Model Learning For Autonomous Racing. 552-563 - Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto:
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation. 564-574 - Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh:
Learning Latent Representations to Influence Multi-Agent Interaction. 575-588 - Jun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert:
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments. 589-603 - Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum:
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. 604-626 - Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu:
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection. 627-641 - Kai Ploeger, Michael Lutter, Jan Peters:
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards. 642-653 - Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames:
Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions. 654-670 - Peter Anderson, Ayush Shrivastava, Joanne Truong, Arjun Majumdar, Devi Parikh, Dhruv Batra, Stefan Lee:
Sim-to-Real Transfer for Vision-and-Language Navigation. 671-681 - Snehal Jauhri, Carlos Celemin, Jens Kober:
Interactive Imitation Learning in State-Space. 682-692 - Lucas Manuelli, Yunzhu Li, Peter R. Florence, Russ Tedrake:
Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning. 693-710 - Rose E. Wang, J. Chase Kew, Dennis Lee, Tsang-Wei Edward Lee, Tingnan Zhang, Brian Ichter, Jie Tan, Aleksandra Faust:
Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous. 711-725 - Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee:
Transporter Networks: Rearranging the Visual World for Robotic Manipulation. 726-747 - Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Assisted Perception: Optimizing Observations to Communicate State. 748-764 - Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. 765-781 - Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Vainavi Viswanath, Michael Laskey, Joseph Gonzalez, Ken Goldberg:
Untangling Dense Knots by Learning Task-Relevant Keypoints. 782-800 - Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh:
Safe Policy Learning for Continuous Control. 801-821 - Mohit Sharma, Jacky Liang, Jialiang Zhao, Alex LaGrassa, Oliver Kroemer:
Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation. 822-844 - Mohit Sharma, Oliver Kroemer:
Relational Learning for Skill Preconditions. 845-861 - Bruno Ferreira de Brito, Hai Zhu, Wei Pan, Javier Alonso-Mora:
Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting Pedestrians. 862-872 - Liuyue Xie, Tomotake Furuhata, Kenji Shimada:
MuGNet: Multi-Resolution Graph Neural Network for Segmenting Large-Scale Pointclouds. 873-882 - Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg:
Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion. 883-894 - Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov:
TNT: Target-driven Trajectory Prediction. 895-904 - Yutao Han, Jacopo Banfi, Mark Campbell:
Planning Paths Through Unknown Space by Imagining What Lies Therein. 905-914 - Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Alexandre Galashov, Nicolas Heess, Francesco Nori:
Learning Dexterous Manipulation from Suboptimal Experts. 915-934 - Carolyn Matl, Yashraj S. Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos:
STReSSD: Sim-To-Real from Sound for Stochastic Dynamics. 935-958 - Xiao Ma, Siwei Chen, David Hsu, Wee Sun Lee:
Contrastive Variational Reinforcement Learning for Complex Observations. 959-972 - Sean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun:
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs. 973-983 - Girish Joshi, Jasvir Virdi, Girish Chowdhary:
Asynchronous Deep Model Reference Adaptive Control. 984-1000 - Sushant Veer, Anirudha Majumdar:
Probably Approximately Correct Vision-Based Planning using Motion Primitives. 1001-1014 - Maria Bauzá Villalonga, Alberto Rodriguez, Bryan Lim, Eric Valls, Theo Sechopoulos:
Tactile Object Pose Estimation from the First Touch with Geometric Contact Rendering. 1015-1029 - Yufei Wang, Gautham Narayan Narasimhan, Xingyu Lin, Brian Okorn, David Held:
ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning. 1030-1048 - Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Jan Achterhold
Sample-efficient Cross-Entropy Method for Real-time Planning. 1049-1065 - Sandeep Singh Sandha, Luis Garcia, Bharathan Balaji, Fatima M. Anwar, Mani B. Srivastava:
Sim2Real Transfer for Deep Reinforcement Learning with Stochastic State Transition Delays. 1066-1083 - Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller:
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. 1084-1099 - Sadegh Rabiee, Joydeep Biswas:
IV-SLAM: Introspective Vision for Simultaneous Localization and Mapping. 1100-1109 - Sehoon Ha, Peng Xu, Zhenyu Tan, Sergey Levine, Jie Tan:
Learning to Walk in the Real World with Minimal Human Effort. 1110-1120 - Nicolás Cruz, Javier Ruiz-del-Solar:
Generation of Realistic Images for Learning in Simulation using FeatureGAN. 1121-1136 - Felix Schiel, Annette Hagengruber, Jörn Vogel, Rudolph Triebel:
Incremental learning of EMG-based control commands using Gaussian Processes. 1137-1146 - Yunlong Song, Selim Naji, Elia Kaufmann, Antonio Loquercio, Davide Scaramuzza:
Flightmare: A Flexible Quadrotor Simulator. 1147-1157 - Tianjian Chen, Zhanpeng He, Matei T. Ciocarlie:
Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learning. 1158-1173 - Davi Frossard, Shun Da Suo, Sergio Casas, James Tu, Raquel Urtasun:
StrObe: Streaming Object Detection from LiDAR Packets. 1174-1183 - Jialiang Zhao, Daniel Troniak, Oliver Kroemer:
Towards Robotic Assembly by Predicting Robust, Precise and Task-oriented Grasps. 1184-1194 - Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. 1195-1210 - Muhammad Haris, Mathias Franzius, Ute Bauer-Wersing, Sai Krishna Kaushik Karanam:
Visual Localization and Mapping with Hybrid SFA. 1211-1220 - Takayuki Murooka, Masashi Hamaya, Felix von Drigalski, Kazutoshi Tanaka, Yoshihisa Ijiri:
EXI-Net: EXplicitly/Implicitly Conditioned Network for Multiple Environment Sim-to-Real Transfer. 1221-1230 - Wout Boerdijk, Martin Sundermeyer, Maximilian Durner
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions. 1231-1245 - Zihao Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine:
MELD: Meta-Reinforcement Learning from Images via Latent State Models. 1246-1261 - Letian Chen, Rohan R. Paleja, Matthew C. Gombolay:
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression. 1262-1277 - Alexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman:
Stein Variational Model Predictive Control. 1278-1297 - Giovanni Franzese, Carlos Celemin, Jens Kober:
Learning Interactively to Resolve Ambiguity in Reference Frame Selection. 1298-1311 - Le Chen, Yunke Ao, Florian Tschopp, Andrei Cramariuc
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning. 1312-1325 - Bhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos:
A User's Guide to Calibrating Robotic Simulators. 1326-1340 - Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani:
Learning Stability Certificates from Data. 1341-1350 - Lars Lindemann, Haimin Hu
Learning Hybrid Control Barrier Functions from Data. 1351-1370 - Lingyao Zhang, Po-Hsun Su, Jerrick Hoang, Galen Clark Haynes, Micol Marchetti-Bowick:
Map-Adaptive Goal-Based Trajectory Prediction. 1371-1383 - Shurjo Banerjee, Jesse Thomason, Jason J. Corso:
The RobotSlang Benchmark: Dialog-guided Robot Localization and Navigation. 1384-1393 - Jan Blumenkamp, Amanda Prorok:
The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learning. 1394-1414 - Martina Zambelli, Yusuf Aytar, Francesco Visin, Yuxiang Zhou, Raia Hadsell:
Learning rich touch representations through cross-modal self-supervision. 1415-1425 - Allen Z. Ren, Sushant Veer, Anirudha Majumdar:
Generalization Guarantees for Imitation Learning. 1426-1442 - Tianchen Ji, Sri Theja Vuppala, Girish Chowdhary, Katherine Rose Driggs-Campbell:
Multi-Modal Anomaly Detection for Unstructured and Uncertain Environments. 1443-1455 - Emmanuel Pignat, Hakan Girgin, Sylvain Calinon:
Generative adversarial training of product of policies for robust and adaptive movement primitives. 1456-1470 - Jarrett Holtz, Arjun Guha, Joydeep Biswas:
Robot Action Selection Learning via Layered Dimension Informed Program Synthesis. 1471-1480 - Dian Wang, Colin Kohler, Robert Platt Jr.:
Policy learning in SE(3) action spaces. 1481-1497 - William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos, Siddhartha S. Srinivasa:
Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity. 1498-1508 - David Surovik, Oliwier Melon, Mathieu Geisert, Maurice F. Fallon, Ioannis Havoutis:
Learning an Expert Skill-Space for Replanning Dynamic Quadruped Locomotion over Obstacles. 1509-1518 - Dawei Sun, Susmit Jha, Chuchu Fan:
Learning Certified Control Using Contraction Metric. 1519-1539 - Adithyavairavan Murali, Weiyu Liu, Kenneth Marino, Sonia Chernova, Abhinav Gupta:
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping. 1540-1557 - Ajay Kumar Tanwani:
DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer. 1558-1571 - Kevin Chen, Nithin Shrivatsav Srikanth, David Kent, Harish Ravichandar, Sonia Chernova:
Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations. 1572-1581 - Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. 1582-1601 - Michel Breyer, Jen Jen Chung, Lionel Ott, Roland Siegwart, Juan I. Nieto:
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter. 1602-1611 - Glen Chou, Dmitry Berenson, Necmiye Ozay:
Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations. 1612-1639 - Hai Nguyen, Brett Daley, Xinchao Song
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability. 1640-1653 - Paul Duckworth, Bruno Lacerda, Nick Hawes:
Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes. 1654-1668 - Hsiao-Yu Tung, Zhou Xian, Mihir Prabhudesai, Shamit Lal, Katerina Fragkiadaki:
3D-OES: Viewpoint-Invariant Object-Factorized Environment Simulators. 1669-1683 - Ayzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev:
Learning Object-conditioned Exploration using Distributed Soft Actor Critic. 1684-1695 - Rasmus Laurvig Haugaard, Jeppe Langaa, Christoffer Sloth, Anders Glent Buch:
Fast robust peg-in-hole insertion with continuous visual servoing. 1696-1705 - Christopher Wang, Candace Ross, Yen-Ling Kuo, Boris Katz, Andrei Barbu:
Learning a natural-language to LTL executable semantic parser for grounded robotics. 1706-1718 - Wenxuan Zhou, Sujay Bajracharya, David Held:
PLAS: Latent Action Space for Offline Reinforcement Learning. 1719-1735 - Mike Kasper, Fernando Nobre, Christoffer Heckman, Nima Keivan:
Unsupervised Metric Relocalization Using Transform Consistency Loss. 1736-1745 - Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance:
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery. 1746-1760 - Wenshan Wang, Yaoyu Hu, Sebastian A. Scherer:
TartanVO: A Generalizable Learning-based VO. 1761-1772 - Yitong Deng, Yaorui Zhang, Xingzhe He, Shuqi Yang, Yunjin Tong, Michael Zhang, Daniel M. DiPietro, Bo Zhu:
Soft Multicopter Control Using Neural Dynamics Identification. 1773-1782 - Marcus Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou:
Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs. 1783-1801 - Bradley Saund, Dmitry Berenson:
Diverse Plausible Shape Completions from Ambiguous Depth Images. 1802-1813 - Sushmita Bhattacharya
Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems. 1814-1828 - Valts Blukis, Ross A. Knepper, Yoav Artzi:
Few-shot Object Grounding and Mapping for Natural Language Robot Instruction Following. 1829-1854 - Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Daniela Rus:
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space. 1855-1870 - Manuel Wuthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer:
TriFinger: An Open-Source Robot for Learning Dexterity. 1871-1882 - Jin Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, Peter Stone:
Learning to Improve Multi-Robot Hallway Navigation. 1883-1895 - Mete Akbulut, Erhan Öztop, Muhammet Yunus Seker, Honghu Xue, Ahmet Ercan Tekden, Emre Ugur:
ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing. 1896-1907 - Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova:
Unsupervised Monocular Depth Learning in Dynamic Scenes. 1908-1917 - Achin Jain, Matthew O'Kelly, Pratik Chaudhari, Manfred Morari:
BayesRace: Learning to race autonomously using prior experience. 1918-1929 - Neha Das
Model-Based Inverse Reinforcement Learning from Visual Demonstrations. 1930-1942 - Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski:
Deep Reactive Planning in Dynamic Environments. 1943-1957 - Yuxiao Chen, Ugo Rosolia, Chuchu Fan, Aaron D. Ames, Richard M. Murray:
Reactive motion planning with probabilisticsafety guarantees. 1958-1970 - Chengguang Xu, Christopher Amato, Lawson L. S. Wong:
Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps. 1971-1991 - Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto:
Visual Imitation Made Easy. 1992-2005 - Pushkal Katara, Y. V. S. Harish, Harit Pandya, Abhinav Gupta, AadilMehdi J. Sanchawala, Gourav Kumar, Brojeshwar Bhowmick, K. Madhava Krishna:
DeepMPCVS: Deep Model Predictive Control for Visual Servoing. 2006-2015 - Guangzhi Tang
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control. 2016-2029 - Boshen Niu, Chenxi Wang, Changliu Liu:
Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial Insertion. 2030-2039 - Elie Aljalbout, Ji Chen, Konstantin Ritt, Maximilian Ulmer, Sami Haddadin:
Learning Vision-based Reactive Policies for Obstacle Avoidance. 2040-2054 - Thomas Lew, Marco Pavone:
Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling. 2055-2070 - Sudeep Dasari, Abhinav Gupta:
Transformers for One-Shot Visual Imitation. 2071-2084 - Jiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Patric Jensfelt, Adrien Gaidon:
Self-Supervised 3D Keypoint Learning for Ego-Motion Estimation. 2085-2103 - Son Nguyen, Ozgur S. Oguz, Valentin N. Hartmann, Marc Toussaint:
Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation Planning. 2104-2119 - Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman:
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. 2120-2136 - Sean Gillen, Katie Byl:
Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning. 2137-2147 - Ran Cheng, Christopher Agia, Yuan Ren, Xinhai Li, Bingbing Liu:
S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds. 2148-2161 - Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine:
Chaining Behaviors from Data with Model-Free Reinforcement Learning. 2162-2177 - Xiao Li, Guy Rosman, Igor Gilitschenski, Jonathan A. DeCastro, Cristian Ioan Vasile, Sertac Karaman, Daniela Rus:
Differentiable Logic Layer for Rule Guided Trajectory Prediction. 2178-2194 - Feng Gao, Jincheng Yu, Hao Shen, Yu Wang, Huazhong Yang:
Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes. 2195-2205 - Tanmay Gangwani, Jian Peng, Yuan Zhou:
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity. 2206-2215 - Junha Roh, Christoforos I. Mavrogiannis, Rishabh Madan, Dieter Fox, Siddhartha S. Srinivasa:
Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled Intersections. 2216-2227 - Aniruddh Gopinath Puranic, Jyotirmoy Deshmukh, Stefanos Nikolaidis:
Learning from Demonstrations using Signal Temporal Logic. 2228-2242 - Boris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone:
MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control. 2243-2256 - Kartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman Khetan, Aditya Varma, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya:
Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach. 2257-2267 - Geoffrey Clark, Joseph Campbell, Heni Ben Amor:
Learning Predictive Models for Ergonomic Control of Prosthetic Devices. 2268-2278 - Samuel Pfrommer, Mathew Halm, Michael Posa:
ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representations. 2279-2291 - Giovanni Sutanto, Isabel M. Rayas Fernández, Peter Englert, Ragesh Kumar Ramachandran, Gaurav S. Sukhatme:
Learning Equality Constraints for Motion Planning on Manifolds. 2292-2305 - Florian Voigt, Lars Johannsmeier, Sami Haddadin:
Multi-Level Structure vs. End-to-End-Learning in High-Performance Tactile Robotic Manipulation. 2306-2316 - Robert Lee, Daniel Ward, Vibhavari Dasagi, Akansel Cosgun, Juxi Leitner, Peter Corke:
Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience. 2317-2327 - Bryan Chen, Alexander Sax, Francis Lewis, Iro Armeni, Silvio Savarese, Amir Zamir, Jitendra Malik, Lerrel Pinto:
Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation. 2328-2346 - Ji Woong Kim, Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov:
Towards Autonomous Eye Surgery by Combining Deep Imitation Learning with Optimal Control. 2347-2358 - Zexi Chen, Xuecheng Xu, Yue Wang, Rong Xiong:
Deep Phase Correlation for End-to-End Heterogeneous Sensor Measurements Matching. 2359-2375
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