Topological simultaneous localization and mapping: a survey

Boal, Jaime; Sánchez-Miralles, Álvaro; Arranz, Álvaro

doi:10.1017/s0263574713001070

Cited by 34 publications

(16 citation statements)

References 93 publications

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“…In the context of monocular SLAM, a topological map is an undirected graph of nodes that typically represents keyframes linked together by edges, when shared data associations between the keyframes exists, as depicted in Fig. 3-K. For a survey on topological maps, the reader is referred to [36]. In spite of the appeal of topological maps in scaling well with large scenes, metric information is still required in order to maintain camera pose estimates.…”

Section: Topological/metric Map Generationmentioning

confidence: 99%

Keyframe-based monocular SLAM: design, survey, and future directions

Younes

Asmar

Shammas

et al. 2017

Robotics and Autonomous Systems

150

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Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframebased monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery.

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Section: Topological/metric Map Generationmentioning

confidence: 99%

Keyframe-based monocular SLAM: design, survey, and future directions

Younes

Asmar

Shammas

et al. 2017

Robotics and Autonomous Systems

150

View full text Add to dashboard Cite

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“…This typically combines dead reckoning with landmark recognition in a joint probabilistic estimate of robot and landmark positions (Cummins and Newman, 2008;Davison et al, 2007;Engel et al, 2014;Mur-Artal and Tardos, 2017). However, for long-range autonomous navigation systems, such as self-driving cars, a practical solution is to recover only local geometry, and to link spaces through a topological representation (Boal et al, 2014;Kuipers et al, 2004). Other SLAM approaches do not attempt geometric reconstruction, but learn geometric appearances along trajectories, producing 'topometrical' maps (Badino et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

The internal maps of insects

Webb

2019

Journal of Experimental Biology

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Insect navigation is strikingly geometric. Many species use path integration to maintain an accurate estimate of their distance and direction (a vector) to their nest and can store the vector information for multiple salient locations in the world, such as food sources, in a common coordinate system. Insects can also use remembered views of the terrain around salient locations or along travelled routes to guide return, which is a fundamentally geometric process. Recent modelling of these abilities shows convergence on a small set of algorithms and assumptions that appear sufficient to account for a wide range of behavioural data. Notably, this 'base model' does not include any significant topological knowledge: the insect does not need to recover the information (implicit in their vector memory) about the relationships between salient places; nor to maintain any connectedness or ordering information between view memories; nor to form any associations between views and vectors. However, there remains some experimental evidence not fully explained by this base model that may point towards the existence of a more complex or integrated mental map in insects.

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“…Boal et al. present a thorough and recent survey of topological approaches for SLAM in (Boal, Sanchez‐Miralles, & Arranz, ).…”

Section: Single‐robot Slam: Algorithmsmentioning

confidence: 99%

Multiple-Robot Simultaneous Localization and Mapping: A Review

et al. 2015

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Simultaneous localization and mapping (SLAM) in unknown GPS‐denied environments is a major challenge for researchers in the field of mobile robotics. Many solutions for single‐robot SLAM exist; however, moving to a platform of multiple robots adds many challenges to the existing problems. This paper reviews state‐of‐the‐art multiple‐robot systems, with a major focus on multiple‐robot SLAM. Various issues and problems in multiple‐robot SLAM are introduced, current solutions for these problems are reviewed, and their advantages and disadvantages are discussed.

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Topological simultaneous localization and mapping: a survey

Cited by 34 publications

References 93 publications

Keyframe-based monocular SLAM: design, survey, and future directions

Keyframe-based monocular SLAM: design, survey, and future directions

The internal maps of insects

Multiple-Robot Simultaneous Localization and Mapping: A Review

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