Multi-hierarchical semantic maps for mobile robotics

By Cipriano Galindo, Alessandro Saffiotti, Silvia Coradeschi, P. Buschka, Juan-Antonio Fernández-Madrigal, Javier González. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005

356 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/8c0c9bc29b9657ba5471a06334ea960eaea6403e

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In Aerospace Engineering

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Citations in the corpus

Hydra: A Real-time Spatial Perception System for 3D Scene Graph Construction and Optimization (2022, unknown): “Early work focuses on 2D maps and investigates the use of hierarchical maps to resolve the apparent divide between metric and topological representations [18, 52, 70].”
Towards semantic maps for mobile robots (2008, background): “[12] is a study, also based on 2D data, to combine metric, topological, and semantic aspects in a map.”
Perception, Planning, Control, and Coordination for Autonomous Vehicles (2017, background): “Object based semantic mapping uses the occurrence of key objects to build a semantic understanding of the environments [173,174], where object recognition and classification is often a very important event in object based semantic understanding of the environment.”
Robot task planning using semantic maps (2008, background): “navigation, semantic maps are usually combined with metric and/or topological representations into hybrid maps [7,13].”
Conceptual spatial representations for indoor mobile robots (2008, background): “[10] presents an approach containing two parallel hierarchies, spatial and conceptual, connected through anchoring.”
3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans (2020, methodology): “Note that the spatial hierarchies in [28] and [110] already resemble a scene graph, with less articulated set of nodes and layers.”
A framework for learning semantic maps from grounded natural language descriptions (2014, background): “Many existing solutions (Galindo et al., 2005; Krieg-Brückher et al., 2005; Martínez Mozos et al., 2007; Meger et al., 2008; Vasudevan and Siegwart, 2008; Zender et al., 2008; Hemachandra et al., 2011; Pronobis and Jensfelt, 2012) build on the effectiveness of SLAM by augmenting a low-level metric m”
A Novel Framework for the Design of Change-Detection Systems for Very-High-Resolution Remote Sensing Images (2013, background): “[8], image processing [1], remote sensing [2], [9], video processing [10], automotive [11], neuroscience [12], medical treatment [13]), most of the techniques developed for an application domain may not effectively work on a different domain (i.”
Semantic mapping for mobile robotics tasks: A survey (2015, methodology): “Finally, it is worth mentioning a number of other papers that focus solely on the semantic mapping problem and, therefore, they utilize metric maps existing in the literature [60], [61], [62], [63].”
Towards 3D Point cloud based object maps for household environments (2008, background): “Our scenario is as follows: a robot enters the room and repeatedly turns and makes a sweeping movement with its left arm that has a a laser sensor mounted on its end effector (see Fig.”
Kimera: From SLAM to spatial perception with 3D dynamic scene graphs (2021, methodology): “(2017) extend the framework in (Galindo et al. 2005) to account for uncertain groundings between spatial and semantic elements.”