Fetching the paper…
Reading the bibliography…
Recent advancements in large language models (LLMs) have enabled a new research domain, LLM agents, for solving robotics and planning tasks by leveraging the world knowledge and general reasoning abilities of LLMs obtained during pretraining.
A. Pnueli, “The temporal logic of programs,” in 18th Annual Symposium on Foundations of Computer Science (sfcs 1977) . ieee, 1977, pp. 46–57
1977
Earlier work this paper cites.
H. Barringer, A. Goldberg, K. Havelund, and K. Sen, “Rule-based runtime verification,” in Verification, Model Checking, and Abstract Interpretation: 5th International Conference, VMCAI 2004 Venice, Italy, January 11-13, 2004 Proceedings 5 . Springer, 2004, pp. 44–57
2004
Earlier work this paper cites.
P. Thati and G. Roşu, “Monitoring algorithms for metric temporal logic specifications,” Electronic Notes in Theoretical Computer Science , vol. 113, pp. 145–162, 2005
2005
Earlier work this paper cites.
International Organization for Standardization/International Electrotechnical Commission, “Functional safety of electrical/electronic/programmable electronic safety-related systems - part 1: General requirements,” 2010
2010
Earlier work this paper cites.
V. Raman, C. Lignos, C. Finucane, K. C. Lee, M. P. Marcus, and H. Kress-Gazit, “Sorry dave, i’m afraid i can’t do that: Explaining unachievable robot tasks using natural language.” in Robotics: science and systems , vol. 2, no. 1. Citeseer, 2013, pp. 2–1
2013
Earlier work this paper cites.
T. Reinbacher, K. Y. Rozier, and J. Schumann, “Temporal-logic based runtime observer pairs for system health management of real-time systems,” in Tools and Algorithms for the Construction and Analysis of Systems: 20th International Conference, TACAS 2014 . Springer, 2014, pp. 357–372
2014
Earlier work this paper cites.
P. Moosbrugger, K. Y. Rozier, and J. Schumann, “R2u2: monitoring and diagnosis of security threats for unmanned aerial systems,” Formal Methods in System Design , vol. 51, pp. 31–61, 2017
2017
Earlier work this paper cites.
P. A. Lasota, T. Fong, and J. A. Shah, “A survey of methods for safe human-robot interaction,” Foundations and Trends® in Robotics , vol. 5, no. 4, pp. 261–349, 2017. [Online]. Available: http://dx.doi.org/10.1561/2300000052
2017
Earlier work this paper cites.
H. Kress-Gazit, M. Lahijanian, and V. Raman, “Synthesis for robots: Guarantees and feedback for robot behavior,” Annu. Rev. Control. Robotics Auton. Syst. , vol. 1, pp. 211–236, 2018. [Online]. Available: https://api.semanticscholar.org/CorpusID:65105626
2018
Earlier work this paper cites.
N. Gopalan, D. Arumugam, L. Wong, and S. Tellex, “Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications,” in Proceedings of Robotics: Science and Systems , Pittsburgh, Pennsylvania, 2018
2018
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 Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 8494–8502
2018
Earlier work this paper cites.
A. Shah, S. Li, and J. Shah, “Planning with uncertain specifications (puns),” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 3414–3421, 2020
2020
Earlier work this paper cites.
M. Foughali, S. Bensalem, J. Combaz, and F. Ingrand, “Runtime verification of timed properties in autonomous robots,” in 2020 18th ACM-IEEE International Conference on Formal Methods and Models for System Design (MEMOCODE) . IEEE, 2020, pp. 1–12
2020
Earlier work this paper cites.
R. Patel, E. Pavlick, and S. Tellex, “Grounding language to non-markovian tasks with no supervision of task specifications,” in Robotics: Science and Systems , 2020
2020
Earlier work this paper cites.
H. Kress-Gazit, K. Eder, G. Hoffman, H. Admoni, B. Argall, R. Ehlers, C. Heckman, N. Jansen, R. Knepper, J. Křetínskỳ et al. , “Formalizing and guaranteeing human-robot interaction,” Communications of the ACM , vol. 64, no. 9, pp. 78–84, 2021
2021
Earlier work this paper cites.
C. Menghi, C. Tsigkanos, P. Pelliccione, C. Ghezzi, and T. Berger, “Specification patterns for robotic missions,” IEEE Transactions on Software Engineering , vol. 47, no. 10, pp. 2208–2224, oct 2021
2021
Cited alongside, same era.
2022
Cited alongside, same era.
A. Pacheck and H. Kress-Gazit, “Physically-feasible repair of reactive, linear temporal logic-based, high-level tasks,” 2022
2022
Cited alongside, same era.
X. Mao, X. Li, Y. Huang, J. Shi, and Y. Zhang, “Programmable logic controllers past linear temporal logic for monitoring applications in industrial control systems,” IEEE Transactions on Industrial Informatics , vol. 18, no. 7, pp. 4393–4405, 2022
2022
Cited alongside, same era.
L. Wang, C. Ma, X. Feng, Z. Zhang, H. Yang, J. Zhang, Z. Chen, J. Tang, X. Chen, Y. Lin, W. X. Zhao, Z. Wei, and J.-R. Wen, “A survey on large language model based autonomous agents,” 2023
2023
Closest in time.
S. Gu, L. Yang, Y. Du, G. Chen, F. Walter, J. Wang, Y. Yang, and A. Knoll, “A review of safe reinforcement learning: Methods, theory and applications,” 2023
2023
Closest in time.
B. Greenman, S. Saarinen, T. Nelson, and S. Krishnamurthi, “Little tricky logic: Misconceptions in the understanding of ltl,” The Art, Science, and Engineering of Programming , vol. 7, 2023
2023
Closest in time.
W. Huang, F. Xia, D. Shah, D. Driess, A. Zeng, Y. Lu, P. Florence, I. Mordatch, S. Levine, K. Hausman, and B. Ichter, “Grounded decoding: Guiding text generation with grounded models for robot control,” 2023
2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, C. Fu, K. Gopalakrishnan, K. Hausman, A. Herzog, D. Ho, J. Hsu, J. Ibarz, B. Ichter, A. Irpan, E. Jang, R. J. Ruano, K. Jeffrey, S. Jesmonth, N. J. Joshi, R. Julian, D. Kalashnikov, Y. Kuang, K.-H. Lee, S. Levine, Y. Lu, L. Luu, C. Parada, P. Pastor, J. Quiambao, K. Rao, J. Rettinghouse, D. Reyes, P. Sermanet, N. Sievers, C. Tan, A. Toshev, V. Vanhoucke, F. Xia, T. Xiao, P. Xu, S. Xu, M. Yan, and A. Zeng, “Do as i can, not as i say: Grounding language in robotic affordances,” 2022
2022
Cited alongside, same era.
W. Huang, F. Xia, T. Xiao, H. Chan, J. Liang, P. Florence, A. Zeng, J. Tompson, I. Mordatch, Y. Chebotar, P. Sermanet, N. Brown, T. Jackson, L. Luu, S. Levine, K. Hausman, and B. Ichter, “Inner monologue: Embodied reasoning through planning with language models,” 2022
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,” 2022
2022
Cited alongside, same era.
B. Chen, F. Xia, B. Ichter, K. Rao, K. Gopalakrishnan, M. S. Ryoo, A. Stone, and D. Kappler, “Open-vocabulary queryable scene representations for real world planning,” 2022
2022
Cited alongside, same era.
D. Shah, B. Osinski, B. Ichter, and S. Levine, “Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,” 2022
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
H. Cherukuri, A. Ferrari, and P. Spoletini, “Towards explainable formal methods: From ltl to natural language with neural machine translation,” in Requirements Engineering: Foundation for Software Quality , V. Gervasi and A. Vogelsang, Eds. Cham: Springer International Publishing, 2022, pp. 79–86
2022
Cited alongside, same era.
J. Wu, R. Antonova, A. Kan, M. Lepert, A. Zeng, S. Song, J. Bohg, S. Rusinkiewicz, and T. Funkhouser, “Tidybot: Personalized robot assistance with large language models,” 2023
2023
Closest in time.
S. Vemprala, R. Bonatti, A. Bucker, and A. Kapoor, “Chatgpt for robotics: Design principles and model abilities,” 2023
2023
Closest in time.
B. Liu, Y. Jiang, X. Zhang, Q. Liu, S. Zhang, J. Biswas, and P. Stone, “Llm+p: Empowering large language models with optimal planning proficiency,” 2023
2023
Closest in time.
Y. Xie, C. Yu, T. Zhu, J. Bai, Z. Gong, and H. Soh, “Translating natural language to planning goals with large-language models,” 2023
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
J. X. Liu, Z. Yang, I. Idrees, S. Liang, B. Schornstein, S. Tellex, and A. Shah, “Lang2ltl: Translating natural language commands to temporal robot task specification,” 2023
2023
Closest in time.
S. Yao, J. Zhao, D. Yu, N. Du, I. Shafran, K. Narasimhan, and Y. Cao, “React: Synergizing reasoning and acting in language models,” 2023
2023
Closest in time.
Z. Ji, N. Lee, R. Frieske, T. Yu, D. Su, Y. Xu, E. Ishii, Y. J. Bang, A. Madotto, and P. Fung, “Survey of hallucination in natural language generation,” ACM Computing Surveys , vol. 55, no. 12, pp. 1–38, mar 2023. [Online]. Available: https://doi.org/10.1145%2F3571730
2023
Closest in time.
OpenAI, “Gpt-4 technical report,” 2023
2023
Closest in time.