EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model

L. P. Kaelbling, “The foundation of efficient robot learning,” Science , vol. 369, no. 6506, pp. 915–916, 2020

2020

Earlier work this paper cites.

A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark et al. , “Learning transferable visual models from natural language supervision,” in International conference on machine learning . PmLR, 2021, pp. 8748–8763

2021

Earlier work this paper cites.

D. Shah, B. Osiński, B. Ichter, Y. Hu, A. Saddiqi et al. , “Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,” in Conference on Robot Learning (CoRL) , 2022

2022

Earlier work this paper cites.

S. Reed, K. Zolna, E. Parisotto, S. Colmenarejo, A. Novikov et al. , “A generalist agent,” arXiv preprint arXiv:2205.06175 , 2022

Original

2022

Earlier work this paper cites.

A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu et al. , “Rt-1: Robotics transformer for real-world control at scale,” arXiv , 2022

2022

Earlier work this paper cites.

W. Huang, F. Xia, J. Tompson, A. Zeng, B. Ichter et al. , “Inner monologue: Embodied reasoning through planning with language models,” in Conference on Robot Learning (CoRL) , 2022

2022

Earlier work this paper cites.

S. Nair, S. Khandelwal, M. Danielczuk, K. Xu, P. Florence et al. , “R3m: A universal visual representation for robot manipulation,” in Conference on Robot Learning (CoRL) , 2022

2022

Earlier work this paper cites.

M. Ahn, A. Brohan, N. Brown, and et al., “Do as i can, not as i say: Grounding language in robotic affordances,” 2022

2022

Earlier work this paper cites.

J. Li, D. Li, S. Savarese, and S. Hoi, “Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,” in International conference on machine learning . PMLR, 2023, pp. 19 730–19 742

2023

Earlier work this paper cites.

J. Liang, W. Huang, F. Xia, P. Xu, K. Hausman, B. Ichter, P. Florence, and A. Zeng, “Code as policies: Language model programs for embodied control,” ICRA , 2023

2023

Earlier work this paper cites.

W. Huang, C. Wang, R. Zhang, Y. Li, J. Wu, and L. Fei-Fei, “Voxposer: Composable 3d value maps for robotic manipulation with language models,” arXiv preprint arXiv:2307.05973 , 2023

Original

2023

Earlier work this paper cites.

A. Brohan, N. Brown, J. Carbajal, and et al., “Rt-2: Vision-language-action models transfer web knowledge to robotic control,” 2023

2023

Earlier work this paper cites.

A. Padalkar, A. Pooley, A. Jain, K. Hausman, A. Rai et al. , “Open x-embodiment: Robotic learning datasets and rt-x models,” in Conference on Robot Learning (CoRL) , 2023

2023

Earlier work this paper cites.

A. Stone, T. Xiao, Y. Lu, K. Gopalakrishnan, K. Hausman et al. , “Open-world object manipulation using pre-trained vision-language models,” in Conference on Robot Learning (CoRL) , 2023

2023

Cited alongside, same era.

T. Xiao, H. Chan, P. Sermanet, A. Wahid, S. Levine et al. , “Robotic skill acquisition via instruction augmentation with vision-language models,” in Robotics: Science and Systems (RSS) , 2023

2023

Cited alongside, same era.

Y. Jiang, A. Gupta, Z. Zhang, G. Wang, L. Fei-Fei et al. , “Vima: General robot manipulation with multimodal prompts,” in International Conference on Machine Learning (ICML) , 2023

2023

Cited alongside, same era.

W. Huang, F. Xia, D. Shah, A. Zeng, P. Florence et al. , “Grounded decoding: Guiding text generation with grounded models for robot control,” in Advances in Neural Information Processing Systems (NeurIPS) , 2023

2023

Cited alongside, same era.

J. Chen, Y. Mu, Q. Yu, T. Wei, S. Wu, Z. Yuan, Z. Liang, C. Yang, K. Zhang, W. Shao et al. , “Roboscript: Code generation for free-form manipulation tasks across real and simulation,” arXiv preprint arXiv:2402.14623 , 2024

Original

2024

Later among the works it cites.

N. Ravi, V. Gabeur, Y.-T. Hu, and et al., “Sam 2: Segment anything in images and videos,” 2024

2024

Later among the works it cites.

Z. Yan, S. Li, Z. Wang, L. Wu, H. Wang, J. Zhu, L. Chen, and J. Liu, “Dynamic open-vocabulary 3d scene graphs for long-term language-guided mobile manipulation,” IEEE Robotics and Automation Letters , 2025

2025

Closest in time.

E. Zhou and Q. e. a. Su, “Code-as-monitor: Constraint-aware visual programming for reactive and proactive robotic failure detection,” in Proceedings of the Computer Vision and Pattern Recognition Conference , 2025, pp. 6919–6929

2025

Closest in time.