The Conference on Robot Learning (CoRL 2021) will take place next week. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford! List of Accepted Papers LILA: Language-Informed Latent Actions Authors : Siddharth Karamcheti*, Megha Srivastava*, Percy Liang, Dorsa Sadigh Contact : skaramcheti@cs.stanford.edu, megha@cs.stanford.edu Keywords : natural language, shared autonomy, human-robot interaction BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments Authors : Sanjana Srivastava*, Chengshu Li*, Michael Lingelbach*, Roberto Martín-Martín*, Fei Xia, Kent Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, C. Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, Li Fei-Fei Contact : sanjana2@stanford.edu Links: Paper | Website Keywords : embodied ai, benchmarking, household activities Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration Authors : Chen Wang, Claudia Pérez-D’Arpino, Danfei Xu, Li Fei-Fei, C. Karen Liu, Silvio Savarese Contact : chenwj@stanford.edu Links: Paper | Website Keywords : learning for human-robot collaboration, imitation learning DiffImpact: Differentiable Rendering and Identification of Impact Sounds Authors : Samuel Clarke, Negin Heravi, Mark Rau, Ruohan Gao, Jiajun Wu, Doug James, Jeannette Bohg Contact : spclarke@stanford.edu Links: Paper | Website Keywords : differentiable sound rendering, auditory scene analysis Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks Authors : Bohan Wu, Suraj Nair, Li Fei-Fei*, Chelsea Finn* Contact : bohanwu@cs.stanford.edu Links: Paper Keywords : model-based reinforcement learning, long-horizon tasks GRAC: Self-Guided and Self-Regularized Actor-Critic Authors : Lin Shao, Yifan You, Mengyuan Yan, Shenli Yuan, Qingyun Sun, Jeannette Bohg Contact : harry473417@ucla.edu Links: Paper | Website Keywords : deep reinforcement learning, q-learning Influencing Towards Stable Multi-Agent Interactions Authors : Woodrow Z. Wang, Andy Shih, Annie Xie, Dorsa Sadigh Contact : woodywang153@gmail.com Award nominations: Oral presentation Links: Paper | Website Keywords : multi-agent interactions, human-robot interaction, non-stationarity Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation Authors : Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, Chelsea Finn Contact : surajn@stanford.edu Links: Paper | Website Keywords : natural language, offline rl, visuomotor manipulation Learning Multimodal Rewards from Rankings Authors : Vivek Myers, Erdem Bıyık, Nima Anari, Dorsa Sadigh Contact : ebiyik@stanford.edu Links: Paper | Video | Website Keywords : reward learning, active learning, learning from rankings, multimodality Learning Reward Functions from Scale Feedback Authors : Nils Wilde*, Erdem Bıyık*, Dorsa Sadigh, Stephen L. Smith Contact : ebiyik@stanford.edu Links: Paper | Video | Website Keywords : preference-based learning, reward learning, active learning, scale feedback Learning to Regrasp by Learning to Place Authors : Shuo Cheng, Kaichun Mo, Lin Shao Contact : lins2@stanford.edu Links: Paper | Website Keywords : regrasping, object placement, robotic manipulation Learning to be Multimodal : Co-evolving Sensory Modalities and Sensor Properties Authors : Rika Antonova, Jeannette Bohg Contact : rika.antonova@stanford.edu Links: Paper Keywords : co-design, multimodal sensing, corl blue sky track O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning Authors : Kaichun Mo, Yuzhe Qin, Fanbo Xiang, Hao Su, Leonidas J. Guibas Contact : kaichun@cs.stanford.edu Links: Paper | Video | Website Keywords : robotic vision, object-object interaction, visual affordance ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations Authors : Ruohan Gao, Yen-Yu Chang, Shivani Mall, Li Fei-Fei, Jiajun Wu Contact : rhgao@cs.stanford.edu Links: Paper | Video | Website Keywords : object dataset, multisensory learning, implicit representations Taskography: Evaluating robot task planning over large 3D scene graphs Authors : Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti Contact : cagia@stanford.edu Links: Paper | Website Keywords : robot task planning, 3d scene graphs, learning to plan, benchmarks What Matters in Learning from Offline Human Demonstrations for Robot Manipulation Authors : Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín Contact : amandlek@cs.stanford.edu Award nominations: Oral Links: Paper | Blog Post | Video | Website Keywords : imitation learning, offline reinforcement learning, robot manipulation XIRL: Cross-embodiment Inverse Reinforcement Learning Authors : Kevin Zakka, Andy Zeng, Pete Florence, Jonathan Tompson, Jeannette Bohg, Debidatta Dwibedi Contact : zakka@berkeley.edu Links: Paper | Website Keywords : inverse reinforcement learning, imitation learning, self-supervised learning iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks Authors : Chengshu Li*, Fei Xia*, Roberto Martín-Martín*, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, Andrey Kurenkov, C. Karen Liu, Hyowon Gweon, Jiajun Wu, Li Fei-Fei, Silvio Savarese Contact : chengshu@stanford.edu Links: Paper | Website Keywords : simulation environment, embodied ai, virtual reality interface Learning Feasibility to Imitate Demonstrators with Different Dynamics Authors : Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh Contact : caozj@cs.stanford.edu Keywords : imitation learning, learning from agents with different dynamics We look forward to seeing you at CoRL 2021!