Robot task planning using semantic maps

By Cipriano Galindo, Juan-Antonio Fernández-Madrigal, Javier González, Alessandro Saffiotti. Robotics Auton. Syst., 2008

325 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/1309243e80811cf652774d0c9ed3ef5d3ae413f3

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In Aerospace Engineering

In Artificial Intelligence

In Computer Networks and Communications

Citations in the corpus

Human–robot interaction review and challenges on task planning and programming (2016, methodology): “An approach based on semantic maps was described in Galindo et al. (2008) and has been evaluated in the case of HRI and robot task planning.”
Semantic mapping for mobile robotics tasks: A survey (2015, background): “How semantic maps aid knowledge representation and vice versa? Ontologies and other knowledge representation schemata can yield full description of the robot’s surroundings, encoding and revealing attributes even when these are not perceivable [108], [115].”
Robot task planning and explanation in open and uncertain worlds (2017, background): “[8], in which a semantic map containing information about typical room-object relationships is used to plan to fill in incomplete information about room types, or the locations of objects.”
Unsupervised discovery of object classes with a mobile robot (2014, unknown): “[9], techniques based on SIFT features (e.”
Combining Optimal Control and Learning for Visual Navigation in Novel Environments (2019, unknown): “To overcome these limitations, task planning approaches have been proposed that leverage object and region speciﬁc semantics during planning [4, 7, 9, 13, 33]; however, often hand-tuned heuristics are used to leverage these semantics in planning.”
Robot task planning and explanation in open and uncertain worlds (2015, background): “[8], in which a semantic map containing information about typical room-object relationships is used to plan to fill in incomplete information about room types, or the locations of objects.”
Place categorization and semantic mapping on a mobile robot (2015, background): “Truly useful robots need to be able to extract semantic information about the place they operate in [1].”
Deliberation for autonomous robots: A survey (2017, methodology): “Astrid [83] POL Semantic Maps Service robots Integration to planning & acting”
Artificial cognition for social human-robot interaction: An implementation (2017, methodology): “Numerous approaches exist, like amodal (in the sense of modality-independent) proxies [54], grounded amodal representations [55], semantic maps [56, 57, 58] or affordance-based planning and object classification [59, 60].”