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Natural language is the most intuitive medium for us to interact with other people when expressing commands and instructions.
C. E. Garcia, D. M. Prett, and M. Morari, “Model predictive control: Theory and practice—a survey,”
1989
Earlier work this paper cites.
P. J. Huber, “Robust estimation of a location parameter,” in
1992
Earlier work this paper cites.
S. M. LaValle,
2006
Earlier work this paper cites.
M. MacMahon, B. Stankiewicz, and B. Kuipers, “Walk the talk: Connecting language, knowledge, and action in route instructions,”
2006
Earlier work this paper cites.
N. Ratliff, M. Zucker, J. A. Bagnell, and S. Srinivasa, “CHOMP: Gradient optimization techniques for efficient motion planning,” in
2009
Earlier work this paper cites.
2011
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
2013
Earlier work this paper cites.
N. H. Kirk, D. Nyga, and M. Beetz, “Controlled natural languages for language generation in artificial cognition,” in
2014
Earlier work this paper cites.
J. L. Ba, J. R. Kiros, and G. E. Hinton, “Layer normalization,”
2016
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,”
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
P. Anderson, Q. Wu, D. Teney, J. Bruce, M. Johnson, N. Sünderhauf, I. Reid, S. Gould, and A. van den Hengel, “Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments,” in
2018
Earlier work this paper cites.
2019
Earlier work this paper cites.
C. Sun, A. Myers, C. Vondrick, K. Murphy, and C. Schmid, “Videobert: A joint model for video and language representation learning,” in
2019
Earlier work this paper cites.
J. Lu, D. Batra, D. Parikh, and S. Lee, “Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,”
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
K. Nguyen and I. Daumé, “Help, anna! visual navigation with natural multimodal assistance via retrospective curiosity-encouraging imitation learning,” 09 2019
2019
Cited alongside, same era.
C.-Y. Ma, Z. Wu, G. AlRegib, C. Xiong, and Z. Kira, “The regretful agent: Heuristic-aided navigation through progress estimation,” in
2019
Cited alongside, same era.
2019
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell
2020
Cited alongside, same era.
H. Alwassel, D. Mahajan, B. Korbar, L. Torresani, B. Ghanem, and D. Tran, “Self-supervised learning by cross-modal audio-video clustering,”
L. Yuan, D. Chen, Y.-L. Chen, N. Codella, X. Dai, J. Gao, H. Hu, X. Huang, B. Li, C. Li
2021
Later among the works it cites.
L. Shao, T. Migimatsu, Q. Zhang, K. Yang, and J. Bohg, “Concept2robot: Learning manipulation concepts from instructions and human demonstrations,”
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
P. Goyal, R. J. Mooney, and S. Niekum, “Zero-shot task adaptation using natural language,”
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2020
Cited alongside, same era.
S. Stepputtis, J. Campbell, M. Phielipp, S. Lee, C. Baral, and H. Ben Amor, “Language-conditioned imitation learning for robot manipulation tasks,”
2020
Cited alongside, same era.
J. Arkin, D. Park, S. Roy, M. R. Walter, N. Roy, T. M. Howard, and R. Paul, “Multimodal estimation and communication of latent semantic knowledge for robust execution of robot instructions,”
2020
Cited alongside, same era.
S. Tellex, N. Gopalan, H. Kress-Gazit, and C. Matuszek, “Robots that use language,”
2020
Cited alongside, same era.
C. Lynch and P. Sermanet, “Language conditioned imitation learning over unstructured data,”
2020
Cited alongside, same era.
A. Majumdar, A. Shrivastava, S. Lee, P. Anderson, D. Parikh, and D. Batra, “Improving vision-and-language navigation with image-text pairs from the web,” in
2020
Cited alongside, same era.
L. Zhou, H. Palangi, L. Zhang, H. Hu, J. Corso, and J. Gao, “Unified vision-language pre-training for image captioning and vqa,” in
2020
Cited alongside, same era.
W. Hao, C. Li, X. Li, L. Carin, and J. Gao, “Towards learning a generic agent for vision-and-language navigation via pre-training,” in
2020
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
A. Szot, A. Clegg, E. Undersander, E. Wijmans, Y. Zhao, J. Turner, N. Maestre, M. Mukadam, D. S. Chaplot, O. Maksymets
2021
Later among the works it cites.
F. Giuliari, I. Hasan, M. Cristani, and F. Galasso, “Transformer networks for trajectory forecasting,” in
2021
Later among the works it cites.
L. Chen, K. Lu, A. Rajeswaran, K. Lee, A. Grover, M. Laskin, P. Abbeel, A. Srinivas, and I. Mordatch, “Decision transformer: Reinforcement learning via sequence modeling,”
2021
Later among the works it cites.
M. Janner, Q. Li, and S. Levine, “Offline reinforcement learning as one big sequence modeling problem,”
2021
Later among the works it cites.
R. Bonatti, A. Bucker, S. Scherer, M. Mukadam, and J. Hodgins, “Batteries, camera, action! learning a semantic control space for expressive robot cinematography,” in
2021
Later among the works it cites.
2022
Closest in time.
S. Ma, S. Vemprala, W. Wang, J. Gupta, Y. Song, D. McDuff, and A. Kapoor, “Compass: Contrastive multimodal pretraining for autonomous systems,” February 2022
2022
Closest in time.
2022
Closest in time.
M. Shridhar, L. Manuelli, and D. Fox, “Cliport: What and where pathways for robotic manipulation,” in
2022
Closest in time.