Fetching the paper…
Reading the bibliography…
This paper demonstrates how OpenAI's ChatGPT can be used in a few-shot setting to convert natural language instructions into a sequence of executable robot actions.
H. T. Kuhn and W. L. Inequalities, “Related systems,” Annals of Mathematic Studies, Princeton Univ. Press. EEUU
1956
Earlier work this paper cites.
M. L. Minsky, “Minsky’s frame system theory,” in Proceedings of the 1975 Workshop on Theoretical Issues in Natural Language Processing
1975
Earlier work this paper cites.
X. Puig, K. Ra, M. Boben, J. Li, T. Wang, S. Fidler, and A. Torralba, “Virtualhome: Simulating household activities via programs,” in 2018 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
2018
Earlier work this paper cites.
N. Wake, M. Fukumoto, H. Takahashi, and K. Ikeuchi, “Enhancing listening capability of humanoid robot by reduction of stationary ego-noise,” IEEJ Transactions on Electrical and Electronic Engineering
2019
Earlier work this paper cites.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al
2020
Earlier work this paper cites.
P. Pramanick, H. B. Barua, and C. Sarkar, “Decomplex: Task planning from complex natural instructions by a collocating robot,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
N. Wake, K. Sasabuchi, and K. Ikeuchi, “Grasp-type recognition leveraging object affordance,” HOBI–RO-MAN Workshop
2020
Earlier work this paper cites.
K. Sasabuchi, N. Wake, and K. Ikeuchi, “Task-oriented motion mapping on robots of various configuration using body role division,” IEEE Robotics and Automation Letters
2020
Earlier work this paper cites.
S. Tellex, N. Gopalan, H. Kress-Gazit, and C. Matuszek, “Robots that use language,” Annual Review of Control, Robotics, and Autonomous Systems
2020
Earlier work this paper cites.
S. G. Venkatesh, R. Upadrashta, and B. Amrutur, “Translating natural language instructions to computer programs for robot manipulation,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2021
Earlier work this paper cites.
N. Wake, R. Arakawa, I. Yanokura, T. Kiyokawa, K. Sasabuchi, J. Takamatsu, and K. Ikeuchi, “A learning-from-observation framework: One-shot robot teaching for grasp-manipulation-release household operations,” in 2021 IEEE/SICE International Symposium on System Integration (SII)
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
D. Saito, N. Wake, K. Sasabuchi, H. Koike, and K. Ikeuchi, “Contact web status presentation for freehand grasping in mr-based robot-teaching,” in Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction
2021
Earlier work this paper cites.
N. Wake, I. Yanokura, K. Sasabuchi, and K. Ikeuchi, “Verbal focus-of-attention system for learning-from-demonstration,” in 2021 IEEE International Conference on Robotics and Automation (ICRA)
2021
Earlier work this paper cites.
I. Yanaokura, N. Wake, K. Sasabuchi, R. Arakawa, K. Okada, J. Takamatsu, M. Inaba, and K. Ikeuchi, “A multimodal learning-from-observation towards all-at-once robot teaching using task cohesion,” in 2022 IEEE/SICE International Symposium on System Integration (SII)
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
A. K. Kovalev and A. I. Panov, “Application of pretrained large language models in embodied artificial intelligence,” Doklady Mathematics
2022
Cited alongside, same era.
W. Huang, P. Abbeel, D. Pathak, and I. Mordatch, “Language models as zero-shot planners: Extracting actionable knowledge for embodied agents,” in International Conference on Machine Learning
2022
Cited alongside, same era.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2022
Cited alongside, same era.
2022
Cited alongside, same era.
J. Jaroslavceva, N. Wake, K. Sasabuchi, and K. Ikeuchi, “Robot ego-noise suppression with labanotation-template subtraction,” IEEJ Transactions on Electrical and Electronic Engineering
2022
Cited alongside, same era.
2022
Cited alongside, same era.
D. Saito, K. Sasabuchi, N. Wake, J. Takamatsu, H. Koike, and K. Ikeuchi, “Task-grasping from a demonstrated human strategy,” in 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, et al
2022
Cited alongside, same era.
Accessed: 2023-08-05
OpenAI, “Chatgpt.” https://openai.com/blog/chatgpt · 2023
Cited alongside, same era.
2023
Closest in time.
2023
Closest in time.
C. Zhao, S. Yuan, C. Jiang, J. Cai, H. Yu, M. Y. Wang, and Q. Chen, “Erra: An embodied representation and reasoning architecture for long-horizon language-conditioned manipulation tasks,” IEEE Robotics and Automation Letters
2023
Closest in time.
O. Mees, J. Borja-Diaz, and W. Burgard, “Grounding language with visual affordances over unstructured data,” in 2023 IEEE International Conference on Robotics and Automation (ICRA)
2023
Closest in time.
S. Vemprala, R. Bonatti, A. Bucker, and A. Kapoor, “Chatgpt for robotics: Design principles and model abilities,” Microsoft Auton. Syst. Robot. Res
2023
Closest in time.
Accessed: 2023-08-05
Microsoft, “Microsoft azure.” https://azure.microsoft.com/ · 2023
Closest in time.
N. Wake, D. Saito, K. Sasabuchi, H. Koike, and K. Ikeuchi, “Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching,” Machine Vision and Applications
2023
Closest in time.
K. Ikeuchi, J. Takamatsu, K. Sasabuchi, N. Wake, and A. Kanehira, “Applying learning-from-observation to household service robots: three common-sense formulations,” arXiv preprint
2023
Closest in time.
N. Wake, A. Kanehira, K. Sasabuchi, J. Takamatsu, and K. Ikeuchi, “Interactive task encoding system for learning-from-observation,” in 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
2023
Closest in time.
2023
Closest in time.
Y. Ye, H. You, and J. Du, “Improved trust in human-robot collaboration with chatgpt,” IEEE Access
2023
Closest in time.
2023
Closest in time.
Accessed: 2023-08-05
Microsoft, “Azure openai - data privacy.” https://learn.microsoft.com/en-us/legal/cognitive-services/openai/data-privacy · 2023
Closest in time.
Accessed: 2023-08-05
OpenAI, “Gpt-4.” https://openai.com/research/gpt-4 · 2023
Closest in time.