Environmental modeling with fingerprint sequences for topological global localization

Lamon, Pierre; Tapus, Adriana; Glauser, E.; Tomatis, N.; Siegwart, Roland

doi:10.1109/iros.2003.1249743

Cited by 35 publications

(36 citation statements)

References 14 publications

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“…Amongst the most similar to our previous contribution -FACT [1], is the fingerprint of a place [25], [26]. Both fingerprint and FACT use segments from unwrapped panoramic images.…”

Section: Introductionmentioning

confidence: 77%

“…As for color features, beside the fingerprint of place [25], a detailed report on the state-of-art can be found in [40].…”

Section: Further Related Workmentioning

confidence: 99%

“…Both fingerprint and FACT use segments from unwrapped panoramic images. The difference is that both [25] and [26] used laser range finder to help the matching of the descriptors, and FACT used only color information from the segments.…”

Section: Introductionmentioning

confidence: 99%

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DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera

Liu

Siegwart

2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-Topological mapping and scene recognition problems are still challenging, especially for online realtime visionbased applications. We develop a hierarchical probabilistic model to tackle them using color information. This work is stimulated by our previous work [1] which defined a lightweight descriptor using color and geometry information from segmented panoramic images. Our novel model uses a Dirichlet Process Mixture Model to combine color and geometry features which are extracted from omnidirectional images. The inference of the model is based on an approximation of conditional probabilities of observations given estimated models. It allows online inference of the mixture model in real-time (at 50Hz), which outperforms other existing approaches. A real experiment is carried out on a mobile robot equipped with an omnidirectional camera. The results show the competence against the state-of-art.

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“…Amongst the most similar to our previous contribution -FACT [1], is the fingerprint of a place [25], [26]. Both fingerprint and FACT use segments from unwrapped panoramic images.…”

Section: Introductionmentioning

confidence: 77%

“…As for color features, beside the fingerprint of place [25], a detailed report on the state-of-art can be found in [40].…”

Section: Further Related Workmentioning

confidence: 99%

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DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera

Liu

Siegwart

2012

2012 IEEE International Conference on Robotics and Automation

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“…The idea of this approach is similar to the topological or fingerprint mapping used for robot navigation and localization [22], which compares perceptional object-features with known database data (for place description) to estimate a robot's current position. It's also similar to the role-based classification approach mentioned by Beer et al [31], which classifies an unknown object by comparing its attribute sets with the known attribute templates.…”

Section: Search Modes For Hidden Objectsmentioning

confidence: 99%

Home‐Explorer: Ontology‐Based Physical Artifact Search and Hidden Object Detection System

Guo

Satake

Imai

2008

Mobile Information Systems

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Abstract.A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects) in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.

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“…Fingerprints of places (i.e. circular list of significant features around the robot) have been proven to be a very promising approach towards effective place characterization and hence environment modelling [9,12,13]. In this work, we choose to use as significant feature: colour bins and vertical edges from the visual information and corners from the laser scanner.…”

Section: Fingerprints Of Placesmentioning

confidence: 99%

A cognitive modeling of space using fingerprints of places for mobile robot navigation

Tapus

Siegwart

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

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-In this work we address the problem of perception, spatial cognition and topological navigation for a mobile robot. The objective of this work is to enable the navigation of an autonomous mobile robot (or vehicle) in an indoor (or outdoor) structured environment without relying on maps a priori learned and without using artificial landmarks. A new method for incremental and automatic topological mapping and global localization using fingerprints of places is presented. The fingerprint-based representation permits a reliable, compact and distinctive environment-modeling. Experimental results for mapping indoor and outdoor environments with a mobile robot and a "SMART" vehicle, both equipped with a multi-sensor system composed of two 180° laser range finders and an omnidirectional camera are also reported.

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Environmental modeling with fingerprint sequences for topological global localization

Cited by 35 publications

References 14 publications

DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera

DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera

Home‐Explorer: Ontology‐Based Physical Artifact Search and Hidden Object Detection System

A cognitive modeling of space using fingerprints of places for mobile robot navigation

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