Octree-based localization using RGB-D data for indoor robots

Martı́n, Francisco; Olivera, Vicente Matellán; Rodriguez, Francisco J.; Ginés, Jonatan

doi:10.1016/j.engappai.2018.10.002

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…The idea is to consider a system in which the robot sensors estimate the position of a marked element in the workspace of the robot. A solution implemented by the team Martín, Matellán, Rodríguez, and Ginés () is used.…”

Section: Methodsmentioning

confidence: 99%

A context‐awareness model for activity recognition in robot‐assisted scenarios

et al. 2019

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Context awareness in ambient assisted living programmes for the elderly is a cornerstone in the current scenario of noncustomized service robots distributed around the world. This research proposes a context‐awareness system for a human–robot scene interpretation based on seven primary contexts and the American Occupational Therapy Association. The context‐awareness system defined here proposes an inference mechanism for the activity recognition supported on hierarchical Bayesian networks. However, when the information from sensors increases, the computational cost associated also increases. Thus, an evaluation of different Bayesian network models is necessary for decreasing its impact over the robot performance. Two topological models have been modelled and tested using OpenMarkov application: a two‐level approach of an input–observations layer and the activity recognition layer, and a three‐layer model setting apart a primary contexts layer, the input–observations layer, and the activity recognition layer. The qualitative and quantitative results presented here show better performance in terms of memory and memory in a three‐layer model. Besides, its effect on a hybrid architecture of a robotic platform is presented.

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Section: Methodsmentioning

confidence: 99%

A context‐awareness model for activity recognition in robot‐assisted scenarios

et al. 2019

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“…Martin et al [119] applied Monte Carlo based probabilistic self-localization on a map of colored 3D points, organized in an octree. They demonstrated that their algorithm recovered quickly from cases of unknown initial position or kidnappings (the robot was manually displaced from one place of the environment to another).…”

Section: Characteristicsmentioning

confidence: 99%

A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

Morar

Moldoveanu

Mocanu

et al. 2020

Sensors

111

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Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage (use of known environment data), sensing devices, type of detected elements, and localization method. It groups 70 of the most recent and relevant image based indoor localization methods according to the proposed classification and discusses their advantages and drawbacks. It highlights localization methods that also offer orientation information, as this is required by an increasing number of applications of indoor localization (e.g., augmented reality).

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A highly robust automatic 3D reconstruction system based on integrated optimization by point line features

Hou

Fei

2020

Engineering Applications of Artificial Intelligence

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Octree-based localization using RGB-D data for indoor robots

Cited by 6 publications

References 19 publications

A context‐awareness model for activity recognition in robot‐assisted scenarios

A context‐awareness model for activity recognition in robot‐assisted scenarios

A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

A highly robust automatic 3D reconstruction system based on integrated optimization by point line features

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