Table of Contents

• Learning a Decision Module by Imitating Driver's Control BehaviorsJunning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma, Chunxiao Liu, Dahua Lin, Bolei Zhou. 1-10 [doi]
• Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose ForecastingXinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart. 11-20 [doi]
• Neuro-Symbolic Program Search for Autonomous Driving Decision Module DesignJiankai Sun, Hao Sun, Tian Han, Bolei Zhou. 21-30 [doi]
• LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar FusionMeet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sida Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun. 31-48 [doi]
• DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior ReasoningChiho Choi, Srikanth Malla, Abhishek Patil, Joon Hee Choi. 49-63 [doi]
• CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPsRohan Chitnis, Tom Silver, Beomjoon Kim, Leslie Pack Kaelbling, Tomás Lozano-Pérez. 64-79 [doi]
• Augmenting GAIL with BC for sample efficient imitation learningRohit Jena, Changliu Liu, Katia P. Sycara. 80-90 [doi]
• From pixels to legs: Hierarchical learning of quadruped locomotionDeepali Jain, Ken Caluwaerts, Atil Iscen. 91-102 [doi]
• Learning a Decentralized Multi-Arm Motion PlannerHuy Ha, Jingxi Xu, Shuran Song. 103-114 [doi]
• SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural NetworksYan Xu, Zhaoyang Huang, Kwan-Yee Lin, Xinge Zhu, Jianping Shi, Hujun Bao, Guofeng Zhang 0001, Hongsheng Li. 115-125 [doi]
• Learning 3D Dynamic Scene Representations for Robot ManipulationZhenjia Xu, Zhanpeng He, Jiajun Wu 0001, Shuran Song. 126-142 [doi]
• CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow EstimationHengli Wang, Rui Fan 0001, Ming Liu 0001. 143-155 [doi]
• SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy LearningAlbert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto. 156-175 [doi]
• Fit2Form: 3D Generative Model for Robot Gripper Form DesignHuy Ha, Shubham Agrawal, Shuran Song. 176-187 [doi]
• Accelerating Reinforcement Learning with Learned Skill PriorsKarl Pertsch, Youngwoon Lee, Joseph J. Lim. 188-204 [doi]
• Positive-Unlabeled Reward LearningDanfei Xu, Misha Denil. 205-219 [doi]
• GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp DetectionKuang-Yu Jeng, Yueh-Cheng Liu, Zhe Yu Liu, Jen-Wei Wang, Ya-Liang Chang, Hung-Ting Su, Winston H. Hsu. 220-231 [doi]
• Action-based Representation Learning for Autonomous DrivingYi Xiao, Felipe Codevilla, Christopher Pal, Antonio Lopez. 232-246 [doi]
• Task-Relevant Adversarial Imitation LearningKonrad Zolna, Scott E. Reed, Alexander Novikov 0001, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang 0001. 247-263 [doi]
• SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous DrivingMing Zhou, Jun Luo, Julian Villela, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang 0001, Montgomery Alban, Iman Fadakar, Zheng Chen, Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Zhengbang Zhu, Yihan Ni, Nhat M. Nguyen, Mohamed ElSayed, Haitham Ammar, Alexander Imani Cowen-Rivers, Sanjeevan Ahilan, Zheng Tian 0002, Daniel Palenicek, Kasra Rezaee, Peyman Yadmellat, Kun Shao, Dong Chen, Baokuan Zhang, Hongbo Zhang, Jianye Hao, Wulong Liu, Jun Wang. 264-285 [doi]
• Reconfigurable Voxels: A New Representation for LiDAR-Based Point CloudsTai Wang, Xinge Zhu, Dahua Lin. 286-295 [doi]
• Learning Object Manipulation Skills via Approximate State Estimation from Real VideosVladimír Petrík, Makarand Tapaswi, Ivan Laptev, Josef Sivic. 296-312 [doi]
• Integrating Egocentric Localization for More Realistic Point-Goal Navigation AgentsSamyak Datta, Oleksandr Maksymets, Judy Hoffman, Stefan Lee, Dhruv Batra, Devi Parikh. 313-328 [doi]
• PLOP: Probabilistic Polynomial Objects trajectory Prediction for autonomous drivingThibault Buhet, Émilie Wirbel, Andrei Bursuc, Xavier Perrotton. 329-338 [doi]
• Reinforcement Learning with Videos: Combining Offline Observations with InteractionKarl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn. 339-354 [doi]
• Learning Obstacle Representations for Neural Motion PlanningRobin Strudel, Ricardo Garcia Pinel, Justin Carpentier, Jean-Paul Laumond, Ivan Laptev, Cordelia Schmid. 355-364 [doi]
• CLOUD: Contrastive Learning of Unsupervised DynamicsJianren Wang, Yujie Lu, Hang Zhao. 365-376 [doi]
• Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral ObjectsMichael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Ken Goldberg. 377-393 [doi]
• Attention-Privileged Reinforcement LearningSasha Salter, Dushyant Rao, Markus Wulfmeier, Raia Hadsell, Ingmar Posner. 394-408 [doi]
• One Thousand and One Hours: Self-driving Motion Prediction DatasetJohn Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska. 409-418 [doi]
• Recovering and Simulating Pedestrians in the WildZe Yang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun. 419-431 [doi]
• SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object ManipulationXingyu Lin, Yufei Wang, Jake Olkin, David Held. 432-448 [doi]
• S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View ConsistencyMel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz. 449-460 [doi]
• Learning RGB-D Feature Embeddings for Unseen Object Instance SegmentationYu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox. 461-470 [doi]
• Modeling Long-horizon Tasks as Sequential Interaction LandscapesSöeren Pirk, Karol Hausman, Alexander Toshev, Mohi Khansari. 471-484 [doi]
• PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to RewardsPrasoon Goyal, Scott Niekum, Raymond J. Mooney. 485-497 [doi]
• Auxiliary Tasks Speed Up Learning Point Goal NavigationJoel Ye, Dhruv Batra, Erik Wijmans, Abhishek Das. 498-516 [doi]
• Learning hierarchical relationships for object-goal navigationAnwesan Pal, Yiding Qiu, Henrik I. Christensen. 517-528 [doi]
• f-IRL: Inverse Reinforcement Learning via State Marginal MatchingTianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Ben Eysenbach. 529-551 [doi]
• Iterative Semi-parametric Dynamics Model Learning For Autonomous RacingIgnat Georgiev, Christoforos Chatzikomis, Timo Völkl, Joshua Smith 0002, Michael N. Mistry. 552-563 [doi]
• Learning Predictive Representations for Deformable Objects Using Contrastive EstimationWilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto. 564-574 [doi]
• Learning Latent Representations to Influence Multi-Agent InteractionAnnie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh. 575-588 [doi]
• Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed EnvironmentsJun Yamada, Youngwoon Lee, Gautam Salhotra, Karl Pertsch, Max Pflueger, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert. 589-603 [doi]
• The EMPATHIC Framework for Task Learning from Implicit Human FeedbackYuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum. 604-626 [doi]
• Range Conditioned Dilated Convolutions for Scale Invariant 3D Object DetectionAlex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu. 627-641 [doi]
• High Acceleration Reinforcement Learning for Real-World Juggling with Binary RewardsKai Ploeger, Michael Lutter, Jan Peters 0001. 642-653 [doi]
• Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier FunctionsSarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames. 654-670 [doi]
• Sim-to-Real Transfer for Vision-and-Language NavigationPeter Anderson, Ayush Shrivastava, Joanne Truong, Arjun Majumdar, Devi Parikh, Dhruv Batra, Stefan Lee. 671-681 [doi]
• Interactive Imitation Learning in State-SpaceSnehal Jauhri, Carlos Celemin, Jens Kober. 682-692 [doi]
• Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement LearningLucas Manuelli, Yunzhu Li, Peter R. Florence, Russ Tedrake. 693-710 [doi]
• Model-based Reinforcement Learning for Decentralized Multiagent RendezvousRose E. Wang, J. Chase Kew, Dennis Lee 0003, Tsang-Wei Edward Lee, Tingnan Zhang, Brian Ichter, Jie Tan, Aleksandra Faust. 711-725 [doi]
• Transporter Networks: Rearranging the Visual World for Robotic ManipulationAndy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, Johnny Lee. 726-747 [doi]
• Assisted Perception: Optimizing Observations to Communicate StateSiddharth Reddy, Sergey Levine, Anca Dragan. 748-764 [doi]
• Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics LearningVaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann. 765-781 [doi]
• Untangling Dense Knots by Learning Task-Relevant KeypointsJennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Vainavi Viswanath, Michael Laskey, Joseph Gonzalez 0001, Ken Goldberg. 782-800 [doi]
• Safe Policy Learning for Continuous ControlYinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh. 801-821 [doi]
• Learning to Compose Hierarchical Object-Centric Controllers for Robotic ManipulationMohit Sharma, Jacky Liang, Jialiang Zhao, Alex LaGrassa, Oliver Kroemer. 822-844 [doi]
• Relational Learning for Skill PreconditionsMohit Sharma, Oliver Kroemer. 845-861 [doi]
• Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting PedestriansBruno Ferreira de Brito, Hai Zhu, Wei Pan, Javier Alonso-Mora. 862-872 [doi]
• MuGNet: Multi-Resolution Graph Neural Network for Segmenting Large-Scale PointcloudsLiuyue Xie, Tomotake Furuhata, Kenji Shimada. 873-882 [doi]
• Learning a Contact-Adaptive Controller for Robust, Efficient Legged LocomotionXingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Anima Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg. 883-894 [doi]
• TNT: Target-driven Trajectory PredictionHang Zhao, Jiyang Gao, Tian Lan, Chen Sun 0002, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov. 895-904 [doi]
• Planning Paths Through Unknown Space by Imagining What Lies ThereinYutao Han, Jacopo Banfi, Mark Campbell 0001. 905-914 [doi]
• Learning Dexterous Manipulation from Suboptimal ExpertsRae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Alexandre Galashov, Nicolas Heess, Francesco Nori. 915-934 [doi]
• STReSSD: Sim-To-Real from Sound for Stochastic DynamicsCarolyn Matl, Yashraj S. Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos. 935-958 [doi]
• Contrastive Variational Reinforcement Learning for Complex ObservationsXiao Ma 0006, Siwei Chen, David Hsu, Wee Sun Lee. 959-972 [doi]
• Universal Embeddings for Spatio-Temporal Tagging of Self-Driving LogsSean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun. 973-983 [doi]
• Asynchronous Deep Model Reference Adaptive ControlGirish Joshi, Jasvir Virdi, Girish Chowdhary 0001. 984-1000 [doi]
• Probably Approximately Correct Vision-Based Planning using Motion PrimitivesSushant Veer, Anirudha Majumdar. 1001-1014 [doi]
• Tactile Object Pose Estimation from the First Touch with Geometric Contact RenderingMaria Bauzá Villalonga, Alberto Rodriguez, Bryan Lim, Eric Valls, Theo Sechopoulos. 1015-1029 [doi]
• ROLL: Visual Self-Supervised Reinforcement Learning with Object ReasoningYufei Wang, Gautham Narayan Narasimhan, Xingyu Lin, Brian Okorn, David Held. 1030-1048 [doi]
• Sample-efficient Cross-Entropy Method for Real-time PlanningCristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Jan Achterhold, Jörg Stückler, Michal Rolinek, Georg Martius. 1049-1065 [doi]
• Sim2Real Transfer for Deep Reinforcement Learning with Stochastic State Transition DelaysSandeep Singh Sandha, Luis Garcia, Bharathan Balaji, Fatima M. Anwar, Mani B. Srivastava. 1066-1083 [doi]
• Towards General and Autonomous Learning of Core Skills: A Case Study in LocomotionRoland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller. 1084-1099 [doi]
• IV-SLAM: Introspective Vision for Simultaneous Localization and MappingSadegh Rabiee, Joydeep Biswas. 1100-1109 [doi]
• Learning to Walk in the Real World with Minimal Human EffortSehoon Ha, Peng Xu, Zhenyu Tan, Sergey Levine, Jie Tan. 1110-1120 [doi]
• Generation of Realistic Images for Learning in Simulation using FeatureGANNicolás Cruz, Javier Ruiz-del-Solar. 1121-1136 [doi]
• Incremental learning of EMG-based control commands using Gaussian ProcessesFelix Schiel, Annette Hagengruber, Jörn Vogel, Rudolph Triebel. 1137-1146 [doi]
• Flightmare: A Flexible Quadrotor SimulatorYunlong Song, Selim Naji, Elia Kaufmann, Antonio Loquercio, Davide Scaramuzza 0001. 1147-1157 [doi]
• Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement LearningTianjian Chen, Zhanpeng He, Matei T. Ciocarlie. 1158-1173 [doi]
• StrObe: Streaming Object Detection from LiDAR PacketsDavi Frossard, Shun Da Suo, Sergio Casas 0002, James Tu, Raquel Urtasun. 1174-1183 [doi]
• Towards Robotic Assembly by Predicting Robust, Precise and Task-oriented GraspsJialiang Zhao, Daniel Troniak, Oliver Kroemer. 1184-1194 [doi]
• Learning to Communicate and Correct Pose ErrorsNicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun. 1195-1210 [doi]
• Visual Localization and Mapping with Hybrid SFAMuhammad Haris, Mathias Franzius, Ute Bauer-Wersing, Sai Krishna Kaushik Karanam. 1211-1220 [doi]
• EXI-Net: EXplicitly/Implicitly Conditioned Network for Multiple Environment Sim-to-Real TransferTakayuki Murooka, Masashi Hamaya, Felix Von Drigalski, Kazutoshi Tanaka, Yoshihisa Ijiri. 1221-1230 [doi]
• Self-Supervised Object-in-Gripper Segmentation from Robotic MotionsWout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel. 1231-1245 [doi]
• MELD: Meta-Reinforcement Learning from Images via Latent State ModelsZihao Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine. 1246-1261 [doi]
• Learning from Suboptimal Demonstration via Self-Supervised Reward RegressionLetian Chen, Rohan R. Paleja, Matthew C. Gombolay. 1262-1277 [doi]
• Stein Variational Model Predictive ControlAlexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman. 1278-1297 [doi]
• Learning Interactively to Resolve Ambiguity in Reference Frame SelectionGiovanni Franzese, Carlos Celemin, Jens Kober. 1298-1311 [doi]
• Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement LearningLe Chen, Yunke Ao, Florian Tschopp, Andrei Cramariuc, Michel Breyer, Jen Jen Chung, Roland Siegwart, César Cadena 0001. 1312-1325 [doi]
• A User's Guide to Calibrating Robotic SimulatorsBhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos. 1326-1340 [doi]
• Learning Stability Certificates from DataNicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani. 1341-1350 [doi]
• Learning Hybrid Control Barrier Functions from DataLars Lindemann, Haimin Hu, Alexander Robey, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, Nikolai Matni. 1351-1370 [doi]
• Map-Adaptive Goal-Based Trajectory PredictionLingyao Zhang, Po-Hsun Su, Jerrick Hoang, Galen Clark Haynes, Micol Marchetti-Bowick. 1371-1383 [doi]
• The RobotSlang Benchmark: Dialog-guided Robot Localization and NavigationShurjo Banerjee, Jesse Thomason, Jason J. Corso. 1384-1393 [doi]
• The Emergence of Adversarial Communication in Multi-Agent Reinforcement LearningJan Blumenkamp, Amanda Prorok. 1394-1414 [doi]
• Learning rich touch representations through cross-modal self-supervisionMartina Zambelli, Yusuf Aytar, Francesco Visin, Yuxiang Zhou, Raia Hadsell. 1415-1425 [doi]
• Generalization Guarantees for Imitation LearningAllen Z. Ren, Sushant Veer, Anirudha Majumdar. 1426-1442 [doi]
• Multi-Modal Anomaly Detection for Unstructured and Uncertain EnvironmentsTianchen Ji, Sri Theja Vuppala, Girish Chowdhary 0001, Katherine Rose Driggs-Campbell. 1443-1455 [doi]
• Generative adversarial training of product of policies for robust and adaptive movement primitivesEmmanuel Pignat, Hakan Girgin, Sylvain Calinon. 1456-1470 [doi]
• Robot Action Selection Learning via Layered Dimension Informed Program SynthesisJarrett Holtz, Arjun Guha, Joydeep Biswas. 1471-1480 [doi]
• Policy learning in SE(3) action spacesDian Wang, Colin Kohler, Robert Platt Jr.. 1481-1497 [doi]
• Amodal 3D Reconstruction for Robotic Manipulation via Stability and ConnectivityWilliam Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos, Siddhartha S. Srinivasa. 1498-1508 [doi]
• Learning an Expert Skill-Space for Replanning Dynamic Quadruped Locomotion over ObstaclesDavid Surovik, Oliwier Melon, Mathieu Geisert, Maurice F. Fallon, Ioannis Havoutis. 1509-1518 [doi]
• Learning Certified Control Using Contraction MetricDawei Sun, Susmit Jha, Chuchu Fan. 1519-1539 [doi]
• Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented GraspingAdithyavairavan Murali, Weiyu Liu, Kenneth Marino, Sonia Chernova, Abhinav Gupta 0001. 1540-1557 [doi]
• DIRL: Domain-Invariant Representation Learning for Sim-to-Real TransferAjay Tanwani. 1558-1571 [doi]
• Learning Hierarchical Task Networks with Preferences from Unannotated DemonstrationsKevin Chen, Nithin Shrivatsav Srikanth, David Kent, Harish Ravichandar, Sonia Chernova. 1572-1581 [doi]
• A Long Horizon Planning Framework for Manipulating Rigid Pointcloud ObjectsAnthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez. 1582-1601 [doi]
• Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in ClutterMichel Breyer, Jen Jen Chung, Lionel Ott, Roland Siegwart, Juan I. Nieto 0001. 1602-1611 [doi]
• Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from DemonstrationsGlen Chou, Dmitry Berenson, Necmiye Ozay. 1612-1639 [doi]
• Belief-Grounded Networks for Accelerated Robot Learning under Partial ObservabilityHai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt. 1640-1653 [doi]
• Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian ProcessesPaul Duckworth, Bruno Lacerda, Nick Hawes. 1654-1668 [doi]
• 3D-OES: Viewpoint-Invariant Object-Factorized Environment SimulatorsHsiao-Yu Tung, Zhou Xian, Mihir Prabhudesai, Shamit Lal, Katerina Fragkiadaki. 1669-1683 [doi]
• Learning Object-conditioned Exploration using Distributed Soft Actor CriticAyzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev. 1684-1695 [doi]
• Fast robust peg-in-hole insertion with continuous visual servoingRasmus Laurvig Haugaard, Jeppe Langaa, Christoffer Sloth, Anders Glent Buch. 1696-1705 [doi]
• Learning a natural-language to LTL executable semantic parser for grounded roboticsChristopher Wang, Candace Ross, Yen-ling Kuo, Boris Katz, Andrei Barbu. 1706-1718 [doi]
• PLAS: Latent Action Space for Offline Reinforcement LearningWenxuan Zhou, Sujay Bajracharya, David Held. 1719-1735 [doi]
• Unsupervised Metric Relocalization Using Transform Consistency LossMike Kasper, Fernando Nobre, Christoffer Heckman, Nima Keivan. 1736-1745 [doi]
• MultiPoint: Cross-spectral registration of thermal and optical aerial imageryFlorian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance. 1746-1760 [doi]
• TartanVO: A Generalizable Learning-based VOWenshan Wang, Yaoyu Hu, Sebastian A. Scherer. 1761-1772 [doi]
• Soft Multicopter Control Using Neural Dynamics IdentificationYitong Deng, Yaorui Zhang, Xingzhe He, Shuqi Yang, Yunjin Tong, Michael Zhang, Daniel M. DiPietro, Bo Zhu 0002. 1773-1782 [doi]
• Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEsMarcus Pereira, Ziyi Wang 0001, Ioannis Exarchos, Evangelos A. Theodorou. 1783-1801 [doi]
• Diverse Plausible Shape Completions from Ambiguous Depth ImagesBradley Saund, Dmitry Berenson. 1802-1813 [doi]
• Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair ProblemsSushmita Bhattacharya, Siva Kailas, Sahil Badyal, Stephanie Gil, Dimitri P. Bertsekas. 1814-1828 [doi]
• Few-shot Object Grounding and Mapping for Natural Language Robot Instruction FollowingValts Blukis, Ross A. Knepper, Yoav Artzi. 1829-1854 [doi]
• Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent SpaceWilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Daniela Rus. 1855-1870 [doi]
• TriFinger: An Open-Source Robot for Learning DexterityManuel 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. 1871-1882 [doi]
• Learning to Improve Multi-Robot Hallway NavigationJin Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, Peter Stone. 1883-1895 [doi]
• ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation SharingMete Akbulut, Erhan Öztop, Muhammet Yunus Seker, Hh X, Ahmet E. Tekden, Emre Ugur. 1896-1907 [doi]
• Unsupervised Monocular Depth Learning in Dynamic ScenesHanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova. 1908-1917 [doi]
• BayesRace: Learning to race autonomously using prior experienceAchin Jain, Matthew O'Kelly, Pratik Chaudhari, Manfred Morari. 1918-1929 [doi]
• Model-Based Inverse Reinforcement Learning from Visual DemonstrationsNeha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier. 1930-1942 [doi]
• Deep Reactive Planning in Dynamic EnvironmentsKei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski. 1943-1957 [doi]
• Reactive motion planning with probabilisticsafety guaranteesYuxiao Chen 0001, Ugo Rosolia, Chuchu Fan, Aaron Ames, Richard M. Murray. 1958-1970 [doi]
• Hierarchical Robot Navigation in Novel Environments using Rough 2-D MapsChengguang Xu, Christopher Amato, Lawson L. S. Wong. 1971-1991 [doi]
• Visual Imitation Made EasySarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta 0001, Pieter Abbeel, Lerrel Pinto. 1992-2005 [doi]
• DeepMPCVS: Deep Model Predictive Control for Visual ServoingPushkal Katara, Harish YVS, Harit Pandya, Abhinav Gupta, Aadil Mehdi Sanchawala, Gourav Kumar, Brojeshwar Bhowmick, K. Madhava Krishna. 2006-2015 [doi]
• Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous ControlGuangzhi Tang, Neelesh Kumar, Raymond Yoo, Konstantinos P. Michmizos. 2016-2029 [doi]
• Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial InsertionBoshen Niu, Chenxi Wang, Changliu Liu. 2030-2039 [doi]
• Learning Vision-based Reactive Policies for Obstacle AvoidanceElie Aljalbout, Ji Chen, Konstantin Ritt, Maximilian Ulmer, Sami Haddadin. 2040-2054 [doi]
• Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial SamplingThomas Lew, Marco Pavone. 2055-2070 [doi]
• Transformers for One-Shot Visual ImitationSudeep Dasari, Abhinav Gupta. 2071-2084 [doi]
• Self-Supervised 3D Keypoint Learning for Ego-Motion EstimationJiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Patric Jensfelt, Adrien Gaidon. 2085-2103 [doi]
• Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation PlanningSon Nguyen, Ozgur Oguz, Valentin N. Hartmann, Marc Toussaint. 2104-2119 [doi]
• Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement LearningRyan Julian, Benjamin Swanson, Gaurav Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman. 2120-2136 [doi]
• Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement LearningSean Gillen, Katie Byl. 2137-2147 [doi]
• S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point CloudsRan Cheng, Christopher Agia, Yuan Ren, Xinhai Li, Bingbing Liu. 2148-2161 [doi]
• Chaining Behaviors from Data with Model-Free Reinforcement LearningAvi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine. 2162-2177 [doi]
• Differentiable Logic Layer for Rule Guided Trajectory PredictionXiao Li 0025, Guy Rosman, Igor Gilitschenski, Jonathan A. DeCastro, Cristian Ioan Vasile, Sertac Karaman, Daniela Rus. 2178-2194 [doi]
• Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic ScenesFeng Gao, Jincheng Yu, Hao Shen, Yu Wang, Huazhong Yang. 2195-2205 [doi]
• Harnessing Distribution Ratio Estimators for Learning Agents with Quality and DiversityTanmay Gangwani, Jian Peng 0001, Yuan Zhou 0007. 2206-2215 [doi]
• Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled IntersectionsJunha Roh, Christoforos I. Mavrogiannis, Rishabh Madan, Dieter Fox, Siddhartha S. Srinivasa. 2216-2227 [doi]
• Learning from Demonstrations using Signal Temporal LogicAniruddh Gopinath Puranic, Jyotirmoy Deshmukh, Stefanos Nikolaidis. 2228-2242 [doi]
• MATS: An Interpretable Trajectory Forecasting Representation for Planning and ControlBoris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone. 2243-2256 [doi]
• Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy ApproachKartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman Khetan, Aditya Varma, Ashish Joglekar, Shalabh Bhatnagar, Ashitava Ghosal, Bharadwaj Amrutur, Shishir Kolathaya. 2257-2267 [doi]
• Learning Predictive Models for Ergonomic Control of Prosthetic DevicesGeoffrey Clark, Joseph Campbell, Heni Ben Amor. 2268-2278 [doi]
• ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit RepresentationsSamuel Pfrommer, Mathew Halm, Michael Posa. 2279-2291 [doi]
• Learning Equality Constraints for Motion Planning on ManifoldsGiovanni Sutanto, Isabel M. Rayas Fernández, Peter Englert, Ragesh Kumar Ramachandran, Gaurav S. Sukhatme. 2292-2305 [doi]
• Multi-Level Structure vs. End-to-End-Learning in High-Performance Tactile Robotic ManipulationFlorian Voigt, Lars Johannsmeier, Sami Haddadin. 2306-2316 [doi]
• Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot ExperienceRobert Lee, Daniel Ward, Vibhavari Dasagi, Akansel Cosgun, Juxi Leitner, Peter Corke. 2317-2327 [doi]
• Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and NavigationBryan Chen, Alexander Sax, Francis Lewis, Iro Armeni, Silvio Savarese, Amir Roshan Zamir, Jitendra Malik, Lerrel Pinto. 2328-2346 [doi]
• Towards Autonomous Eye Surgery by Combining Deep Imitation Learning with Optimal ControlJi Woong Kim, Peiyao Zhang, Peter Gehlbach, Iulian Iordachita, Marin Kobilarov. 2347-2358 [doi]
• Deep Phase Correlation for End-to-End Heterogeneous Sensor Measurements MatchingZexi Chen, Xuecheng Xu, Yue Wang 0020, Rong Xiong. 2359-2375 [doi]