Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization

By Howie Choset, K. Nagatani. IEEE Trans. Robotics Autom., 2001

739 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/a5d0d94bf87dd9de4ce9e211e0b9a1516a6ddc59

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Citations in the corpus

Coordinated multi-robot exploration (2005, methodology): “Finally, we discuss related work in Section V.”
Robust Mapping and Localization in Indoor Environments Using Sonar Data (2002, methodology): “Popular choices for the map representation include grid-based (Elfes 1987; Schultz and Adams 1998), topological (Kuipers 2000; Choset and Nagatani 2001), featurebased models (Moutarlier and Chatila 1989; Ayache and Faugeras 1989), and sequential Monte Carlo methods (Thrun 2001; Doucet, de Freitas,…”
Multiple‐Robot Simultaneous Localization and Mapping: A Review (2016, methodology): “(Choset and Nagatani, 2001), (Choset et al.”
Robot task planning using semantic maps (2008, background): “Most of these maps fall into two categories: metric maps [2,3], which represent geometric features of the environment, and topological maps, [4,5] which represent distinctive points and their topological relations.”
CENTRIST: A Visual Descriptor for Scene Categorization (2011, background): “A place in topological maps does not necessarily coincide with the human concept of rooms or regions [6].”
Mobile Robot Localisation and Mapping in Extensive Outdoor Environments (2002, background): “Hybrid topologicalmetric maps [141, 121, 30, 31] are basically topological frameworks where the place definitions and/or path definitions contain metric (as well as qualitative) information.”
Neural Topological SLAM for Visual Navigation (2020, background): “In a similar vein, non-metric topological representations have also been considered in classical literature [10, 20, 23].”
Vision-based global localization and mapping for mobile robots (2005, background): “One of the appealing aspects of a hybrid metrical/topological approach to mapping and localization [5], [6] is that uncertain state estimates need not be referenced to a single global reference frame.”
Cooperative concurrent mapping and localization (2002, background): “Another possibility is to use a topological representation [24], [25].”
Autonomous Vehicle Navigation in Rural Environments Without Detailed Prior Maps (2018, background): “For example, seminal works such as [4] and [5] laid the foundation in this field.”
Simultaneous Localization, Mapping and Moving Object Tracking (2007, background): “…navigation has produced four major paradigms for environment representation: feature-based approaches (Leonard and Durrant-Whyte, 1991), grid-based approaches (Elfes, 1988 Thrun et al., 1998), direct approaches (Lu and Milios, 1994, 1997), and topological approaches (Choset and Nagatani, 2001).”
Adapting the Sample Size in Particle Filters Through KLD-Sampling (2003, background): “The state space of the robot consists of a set of discrete, locally distinctive locations such as corners or crossings of hallways (Kaelbling, Cassandra, and Kurien 1996; Simmons and Koenig 1995; Kuipers 2000; Hertzberg and Kirchner 1996; Choset and Nagatani 2001; Kuipers and Beeson 2002).”
Robotics-Based Location Sensing Using Wireless Ethernet (2002, background): “Another alternative for modeling the environment is with a topological map, represented as a generalized Voronoi graph [6].”
RNN-based Learning of Compact Maps for Efficient Robot Localization (2007, methodology): “To reduce the amount of data in high resolution grid-based mapping some researchers convert the map into a topological map [5, 6].”
Visual odometry (2004, methodology): “This information can be used in conjunction with some sort of map and/or localization technique, such as slam[4], to augment a navigation system and increase the usefulness of the system.”
Simultaneous Localization and Map Building in Large-Scale Cyclic Environments Using the Atlas Framework (2004, background): “One of the appealing aspects of a hybrid metrical/topological approach to mapping and localization (Chong and Kleeman 1997a; Kuipers 2000; Bailey and Nebot 2001; Choset and Nagatani 2001) is that uncertain state estimates do not need to be referenced to a single global reference frame.”