Vision-based pose estimation for indoor navigation of unmanned micro aerial vehicle based on the 3D model of environment

Buyval, Alexander; Gavrilenkov, Mikhail

doi:10.1109/meacs.2015.7414857

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…The description of an algorithm of visual localization which utilizes edges of the images for the main visual characteristic is presented in [1], [2]. These works also introduce the method of likeness evaluation of two images -gathered from sensor and a model.…”

Section: Base Algorithm For Localizationmentioning

confidence: 99%

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Visual Localization for Copter based on 3D Model of Environment with CNN Segmentation

Buyval

Mustafin

Gavrilenkov³

et al. 2018

Proceedings of Information Science and Cloud Computing — PoS(ISCC 2017)

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This paper introduces a novel approach to indoor visual localization based on a particle filter, CNN-segmentation and the nearest edge method for particle weight estimation. A main algorithm is used by detecting the edges on the image from camera and then mapping them to a 3D model of the room. The main contribution of the paper is to introduce a novel approach that allows to get rid of such problems as noise generated by textured objects, edges created by dynamic objects and groups of unexpected objects which are considered to be excessive and can be removed from localization algorithm. The algorithm described in this paper was verified on a computer model in ROS/Gazebo environment. ISCC2017

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Section: Base Algorithm For Localizationmentioning

confidence: 99%

“…In this paper we used 100 particles. Details regarding choosing the number of particles can be found in [1].…”

Section: Base Algorithm For Localizationmentioning

confidence: 99%

Visual Localization for Copter based on 3D Model of Environment with CNN Segmentation

Buyval

Mustafin

Gavrilenkov³

et al. 2018

Proceedings of Information Science and Cloud Computing — PoS(ISCC 2017)

Self Cite

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“…2 Alternatively, vision-based location and pose estimation systems may be more suitable for indoor and outdoor applications. 3,4 Additionally, these systems offer an abundance of data that allow to increase accuracy in uncontrolled environments. However, vision-based systems still require improvements in robustness and operational performance.…”

Section: Introductionmentioning

confidence: 99%

Vision-based pose estimation for robot navigation in an uncontrolled environment

Zheng Wu,

Juarez-Salazar,

Diaz-Ramirez

2023

Optics and Photonics for Information Processing XVII

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Location and pose estimation are essential tasks for robot navigation. Conventional global positioning systems can perform poorly due to environmental or indoor interference. Alternatively, vision-based location and pose estimation systems may be more suitable for indoor and outdoor applications. However, vision-based systems still need to improve their robustness in an uncontrolled environment and operational performance. In this work, a visual pose estimation method for robot navigation in an uncontrolled environment is proposed. The theoretical principles of pose estimation are reviewed and the usefulness of the proposed approach in a navigation sequence is shown. The results obtained show that the proposed method is feasible for robot navigation applications.

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“…This leads to poor scaling for large environment localization and mapping. The recent approaches [14,15,16,17,18] use different constraints (e.i. using keyframes for keypoint matching) to optimize the time required for loop detection and map correction, but their usage is usually limited to specific vSLAM method.…”

Section: Introductionmentioning

confidence: 99%

Original Loop-Closure Detection Algorithm for Monocular vSLAM

Bokovoy

Yakovlev

2017

Lecture Notes in Computer Science

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Abstract. Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays. In this work we study one of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure detection. We analyze the existing methods and propose original algorithm for loop-closure detection, which is suitable for dense, semi-dense and feature-based vSLAM methods. We evaluate the algorithm experimentally and show that it contribute to more accurate mapping while speeding up the monocular vSLAM pipeline to the extent the latter can be used in real-time for controlling small multirotor vehicle (drone).

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Vision-based pose estimation for indoor navigation of unmanned micro aerial vehicle based on the 3D model of environment

Cited by 6 publications

References 6 publications

Visual Localization for Copter based on 3D Model of Environment with CNN Segmentation

Visual Localization for Copter based on 3D Model of Environment with CNN Segmentation

Vision-based pose estimation for robot navigation in an uncontrolled environment

Original Loop-Closure Detection Algorithm for Monocular vSLAM

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