Comparative analysis of ROS-based monocular SLAM methods for indoor navigation

Buyval, Alexander; Afanasyev, Ilya; Magid, Evgeni

doi:10.1117/12.2268809

Cited by 40 publications

(19 citation statements)

References 1 publication

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“…In comparison with the methods of visual SLAM, this method is more robust for a typical office room because it uses typical visual features for this type of room (the edges of walls, windows, doors, etc.). The detailed comparison of different visual SLAM algorithms is presented in [12].…”

Section: Visual Localization For Copter B Ased On 3d Modelmentioning

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)

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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: Visual Localization For Copter B Ased On 3d Modelmentioning

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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“…A variety of applications in robotics employ digital cameras for the purposes of 3D scene reconstruction, obstacle avoidance [1], object detection and tracking [2], visual simultaneous localization and mapping (SLAM) [3], path planning [4], human-robot interaction, teleoperation and in urban search and rescue operations [5], etc. Most of the up-to-date solutions require to use more than just a single on-board camera, for example, stereo SLAM with two monocular cameras [6] and multi-camera rig setup to achieve higher accuracy results.…”

Section: Introductionmentioning

confidence: 99%

ROS-based Multiple Cameras Video Streaming for a Teleoperation Interface of a Crawler Robot

Edgar¹,

Arkadevich²,

Nabiullovich³

et al. 2018

JRNAL

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Digital cameras are being widely used in robotics in 3D scene reconstruction, simultaneous localization and mapping (SLAM), and other applications, which often require real-time video stream from multiple cameras. In a case of a mobile robotic system with limited hardware capabilities performance issues may arise. In this work we present a real-time video streaming robot operating system (ROS) package for our crawler-type mobile robot Servosila Engineer, which has four on-board cameras. Compared to OpenCV based solution our package demonstrates less resource consumption.

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“…Stereo vision is widely used in robotics for navigation, obstacle avoidance and path planning [1], object tracking, 3D scene reconstruction, simultaneous localization and mapping [2]. Calibration of a stereoscopic vision system is a necessary step in 3-D computer vision in order to achieve high accuracy in deriving metric information from 2D images such as distance between objects and their dimensions [3].…”

Section: Introductionmentioning

confidence: 99%

Experiments on mobile robot stereo vision system calibration under hardware imperfection

et al. 2018

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Abstract. Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

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Comparative analysis of ROS-based monocular SLAM methods for indoor navigation

Cited by 40 publications

References 1 publication

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

ROS-based Multiple Cameras Video Streaming for a Teleoperation Interface of a Crawler Robot

Experiments on mobile robot stereo vision system calibration under hardware imperfection

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