Understanding and executing instructions for everyday manipulation tasks from the World Wide Web
By Moritz Tenorth, Daniel Nyga, Michael Beetz. 2010
160 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sergey Levine
- Cordelia Schmid
- Chelsea Finn
- Mohit Bansal
- Pieter Abbeel
- Trevor Darrell
- Ali Farhadi
- Dieter Fox
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Trevor Darrell
- Cordelia Schmid
- Jitendra Malik
- Dacheng Tao
- Li Fei-Fei
- Kristen Grauman
- Abhinav Kumar Gupta
In Natural Language Processing
- Yonatan Bisk
- Dieter Fox
- Mohit Shridhar
- Roozbeh Mottaghi
- Jesse Thomason
- Cordelia Schmid
- Luke S. Zettlemoyer
- Ashutosh Saxena
Citations in the corpus
- Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents (2022, background): “A series of them parse language instructions into formal logic or rely mainly on lexical analysis to resolve various linguistic ambiguities for embodied agents (Artzi & Zettlemoyer, 2013; Misra et al., 2015; 2016; Tenorth et al., 2010).”
- ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks (2019, background): “There, research has focused on mapping instructions to actions [5, 13, 31, 35, 48], but these works do not involve visual, interactive environments.”
- Unsupervised Semantic Parsing of Video Collections (2015, methodology): “Recent methods on natural language processing [40, 58] focus on semantic parsing of language recipes in order to extract actions and the objects in the form of predicates.”
- Robotic roommates making pancakes (2011, methodology): “Using the encyclopedic knowledge base the translation of instructions into robot plans is performed by the following sequence of steps [3].”
- Episodic Transformer for Vision-and-Language Navigation (2021, background): “Building systems to understand and execute human instructions has been the subject of many previous works [7, 8, 10, 12, 37, 41, 46, 47, 52, 62].”
- Envisioning the qualitative effects of robot manipulation actions using simulation-based projections (2017, methodology): “Following our previous work, we represent the environment of the robot with semantic maps (Tenorth et al., 2010a).”
- KnowRob: A knowledge processing infrastructure for cognition-enabled robots (2013, methodology): “There are also many tools and links between OpenCyc and other knowledge bases, for example the links to the WordNet lexical database that were used by Tenorth et al. (2010b).”