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Ruotolo, W., Brouwer, D., & Cutkosky, M. (2021). From Grasping to Manipulation with Gecko-Inspired Adhesives. Science Robotics. https://www.science.org/doi/10.1126/scirobotics.abi9773#.YdTALXyv-tk.mailto
Clarke, S., Heravi, N., Rau, M., Gao, R., Wu, J., James, D., & Bohg, J. (2021). Differentiable Rendering and Identification of Impact Sounds. Conference on Robot Learning (CoRL). https://sites.google.com/view/diffimpact
Wong, J., Tung, A., Kurenkov, A., Mandlekar, A., Li, F.-F., Saverese, S., & Martin-Martin, R. (2021). Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation. Conference on Robot Learning (CoRL) 2021. https://sites.google.com/view/il-for-mm/home
Mandlekar, A., Xu, D., Wong, J., Nasiriany, S., Wang, C., Kulkarni, R., Li, F.-F., Savarese, S., Zhu, Y., & Martin-Martin, R. (2021). What Matters in Learning from Offline Human Demonstrations for Robot Manipulation. CoRL 2021. https://arxiv.org/pdf/2108.03298.pdf
Bhattacharyya, R., Jung, S., Senanayake, R., & Kochenderfer, M. (2021). A hybrid rule-based and data-driven approach to human behavior modeling through particle filtering . IEEE 2021. https://ieeexplore.ieee.org/document/9580542
Luo, Z., Xie, W., Kapoor, S., Liang, Y., Cooper, M., Niebles, J. C., Adeli, E., & Li, F.-F. (2021). MOMA: Multi-Object Multi-Actor Activity Parsing. NeurIPS2021. https://proceedings.neurips.cc/paper/2021/hash/95688ba636a4720a85b3634acfec8cdd-Abstract.html
Yi, B., Lee, M., Kloss, A., Martin-Martin, R., & Bohg, J. (2021). Differentiable Factor Graph Optimization for Learning Smoothers. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://sites.google.com/view/diffsmoothing
Mohanty, A., Zawislak, R., Bhamidipati, S., & Gao, G. (2021). Precise Relative Positioning for Tandem Drifting Cars. ION GNSS+ 2021. https://www.ion.org/publications/abstract.cfm?articleID=17871
Karamcheti, S., Srivastava, M., Liang, P., & Sadigh, D. (2021). LILA: Language-Informed Latent Actions. Conference on Robot Learning (CoRL). https://iliad.stanford.edu/pdfs/publications/karamcheti2021lila.pdf
Srivastava, S., Li, C. ., Lingelbach, M., Martin-Martin, R., Xia, F., Vainio, K., Lian, Z., Gokmen, C., Buch, S., Liu, K., Savarese, S., Gweon, H., Wu, J., & Li, F.-F. (2021). BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments . Conference on Robot Learning (CoRL). https://ckllab.stanford.edu/behavior-benchmark-everyday-household-activities-virtual-interactive-and-ecological-environments
Nair, S., Mitchell, E., Chen, K., Ichter, B., Savarese, S., & Finn, C. (2021). Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation. Conference on Robot Learning. https://arxiv.org/pdf/2109.01115.pdf
Nagami, K., & Schwager, M. (2021). HJB-RL: Initializing Reinforcement Learning with Optimal Control Policies Applied to Autonomous Drone Racing. Robotics: Science and Systems (RSS 2021).
Rempe, D., Birdal, T., Hertzmann, A., Yang, J., Sridhar, S., & Guibas, L. (2021). HuMoR: 3D Human Motion Model for Robust Pose Estimation. nternational Conference on Computer Vision (ICCV). https://geometry.stanford.edu/projects/humor/docs/humor.pdf
Currano, R., Yeon, S., Moore, D., Lyons, K., & Sirkin, D. (2021). Little Road Driving HUD: Heads-Up Display Complexity Influences Drivers’ Perceptions of Automated Vehicles. 2021 ACM CHI Conference on Human Factors in Computing Systems.
Senanayak, R., Beltran Hatch, K., Ziming Zheng, J., & Kochenderfer, M. (2021). 3D Velocity Maps for Uncertain Dynamic Urban Environments. International Conference on Intelligent Robots and Systems 2021.
Ivanovic, B., Lee, K.-H., Tokmakov, P., Wulfe, B., McAllister, R., Gaidon, A., & Pavone, M. (2021). Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. International Conference on Computer Vision (ICCV).
Fang, K., Zhu, Y., Savarese, S., & Li, F.-F. (2021). Learning Generalizable Skills via Automated Generation of Diverse Tasks. Robotics: Science and System 2021.
Ivanovic, B., Leung, K., Schmerling, E., & Pavone, M. (2021). Multimodal Deep Generative Models for Trajectory Prediction: A Conditional VariationalAutoencoder Approach. IEEE Robotics and Automation Letters. https://arxiv.org/abs/2008.03880
Le Cleac’h, S., Schwager, M., & Manchester, Z. (2021). ALGAMES: A Fast Solver for Constrained Dynamic Games. Autonomous Robots (Springer).
Gruebele, A., Lin, M., Brouwer, D., Yuan, S., Zerbe, A., & Cutkosky, M. (2021). A Stretchable Tactile Sleeve for Reaching into Cluttered Spaces. RA-L.