Zeng, Andy

Matterport3D: Learning from RGB-D Data in Indoor Environments

Chang, A., Dai, A., Funkhouser, T., Halber, M., Niebner, M., Savva, M., Song, S., Zeng, A., & Zhang, Y. (2017) · 2017 International Conference on 3D Vision (3DV)

3D Surveying and Cultural Heritage3D Shape Modeling and Analysis

Cited by 1,858

Code as Policies: Language Model Programs for Embodied Control

Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., & Zeng, A. (2022) · arXiv

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 767

Code as Policies: Language Model Programs for Embodied Control

Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., & Zeng, A. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 767

Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning

Zeng, A., Song, S., Welker, S., Lee, J., Rodriguez, A., & Funkhouser, T. (2018) · 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 606

PaLM-E: An Embodied Multimodal Language Model

Driess, D., Xia, F., Sajjadi, M. S. M., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 591

Visual Language Maps for Robot Navigation

Huang, C., Mees, O., Zeng, A., & Burgard, W. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Sensor-Based LocalizationMultimodal Machine Learning Applications

Cited by 376

Inner Monologue: Embodied Reasoning through Planning with Language Models

Huang, W., Xia, F., Xiao, T., Chan, H., Liang, J., Florence, P., Zeng, A., Tompson, J., Mordatch, I., Chebotar, Y., et al. (2022) · arXiv

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 287

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Zeng, A., Attarian, M., Ichter, B., Choromanski, K., Wong, A., Welker, S., Tombari, F., Purohit, A., Ryoo, M., Sindhwani, V., et al. (2022) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 205

Transporter Networks: Rearranging the Visual World for Robotic Manipulation

Zeng, A., Florence, P., Tompson, J., Welker, S., Chien, J., Attarian, M., Armstrong, T., Krasin, I., Duong, D., Wahid, A., et al. (2020) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 200

Grasping in the Wild: Learning 6DoF Closed-Loop Grasping From Low-Cost Demonstrations

Song, S., Zeng, A., Lee, J., & Funkhouser, T. (2020) · IEEE Robotics and Automation Letters

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 185

Implicit Behavioral Cloning

Florence, P., Lynch, C., Zeng, A., Ramirez, O., Wahid, A., Downs, L., Wong, A., Lee, J., Mordatch, I., & Tompson, J. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 131

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks

Seita, D., Florence, P., Tompson, J., Coumans, E., Sindhwani, V., Goldberg, K., & Zeng, A. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 130

What are the important technologies for bin picking? Technology analysis of robots in competitions based on a set of performance metrics

Fujita, M., Domae, Y., Noda, A., Garcia Ricardez, G. A., Nagatani, T., Zeng, A., Song, S., Rodriguez, A., Causo, A., Chen, I. M., et al. (2019) · Advanced Robotics

Robot Manipulation and LearningAdvanced Manufacturing and Logistics Optimization

Cited by 78

Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners

Ren, A. Z., Dixit, A., Bodrova, A., Singh, S., Tu, S., Brown, N., Xu, P., Takayama, L., Xia, F., Varley, J., et al. (2023) · arXiv

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 69

Large Language Models as General Pattern Machines

Mirchandani, S., Xia, F., Florence, P., Ichter, B., Driess, D., Arenas, M. G., Rao, K., Sadigh, D., & Zeng, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

XIRL: Cross-embodiment inverse reinforcement learning

Zakka, K., Zeng, A., Florence, P., Tompson, J., Bohg, J., & Dwibedi, D. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 38

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Li, C., Liang, J., Zeng, A., Chen, X., Hausman, K., Sadigh, D., Levine, S., Fei-Fei, L., Xia, F., & Ichter, B. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Nasiriany, S., Xia, F., Yu, W., Xiao, T., Liang, J., Dasgupta, I., Xie, A., Driess, D., Wahid, A., Xu, Z., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 13