Object localization and tracking based on multiple sensor fusion in intelligent home

Yin, Jianqin; Tian, Guohui; Li, Guodong

doi:10.1109/ccdc.2014.6853120

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Several techniques, such as range-based, range-free, and AI-based, can be used for object identification and localization to perform tasks in a certain environment efficiently. If multiple objects exist in a particular environment, such sensors are essential for identifying and localizing multiple objects simultaneously [1], [2]. These sensors include radiofrequency identification (RFID), laser range finder (LRF), and ultrawideband (UWB) sensors.…”

Section: Introductionmentioning

confidence: 99%

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Ali¹,

Liu²,

He³

et al. 2021

IEEE Access

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Object identification and localization in indoor and outdoor environments are paramount issues in object-human interaction. Recent advancements in the data fusion capabilities of multi-sensor systems have paved the way for research on emerging object identification and positioning techniques. This review describes techniques and methods used in positioning technologies. State-of-the-art localization technologies are classified into range-based, range-free and AI-based categories. An in-depth analysis of localization approaches based on laser range finder, radio-frequency identification, ultra-wideband, inertial measurement unit, etc., are presented by providing a detailed comparison based on range, accuracy, measurement method, advantages, disadvantages, and their applications. Furthermore, we investigate stateof-the-art multimodal data fusion techniques that utilize probabilistic methods for the precise estimation of object identification in motion and its localization.INDEX TERMS Indoor and outdoor positioning systems; identification and localization; unstructured environment; multi-sensor system; multi-object; positioning and localization techniques.

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Section: Introductionmentioning

confidence: 99%

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Ali¹,

Liu²,

He³

et al. 2021

IEEE Access

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“…22 There are some reported works on motion estimation with binocular divergent systems, 23 trinocular divergence for visual odometry for robots, 24 and divergent visual simultaneous localization and mapping (SLAM) 25 in mobile robots. In contrast to active sensing modalities for localization, 26,27 object detection, 28 and SLAM 29 with parallel multiple views, 30 this work estimates the posture of a 4WD WMR by exploiting sensor fusion feedback using a radial trinocular sensor. Numerous visual odometry algorithms have been reported, 31 using stereo cameras, 32 matching multi-frame features, 33 local structural invariants, 34 three-dimensional (3D) point clouds, 35 and outdoor approaches such as urban 36 and train 37 environments.…”

Section: Introductionmentioning

confidence: 99%

Divergent trinocular vision observers design for extended Kalman filter robot state estimation

Martínez‐García

Rivero-Juárez

Torres-Méndez

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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Here, we report the design of two deterministic observers that exploit the capabilities of a home-made divergent trinocular visual sensor to sense depth data. The three-dimensional key points that the observers can measure are triangulated for visual odometry and estimated by an extended Kalman filter. This work deals with a four-wheel-drive mobile robot with four passive suspensions. The direct and inverse kinematic solutions are deduced and used for the updating and prediction models of the extended Kalman filter as feedback for the robot’s position controller. The state-estimation visual odometry results were compared with the robot’s dead-reckoning kinematics, and both are combined as a recursive position controller. One observer model design is based on the analytical geometric multi-view approach. The other observer model has fundamentals on multi-view lateral optical flow, which was reformulated as nonspatial–temporal and is modeled by an exponential function. This work presents the analytical deductions of the models and formulations. Experimental validation deals with five main aspects: multi-view correction, a geometric observer for range measurement, an optical flow observer for range measurement, dead-reckoning and visual odometry. Furthermore, comparison of positioning includes a four-wheel odometer, deterministic visual observers and the observer–extended Kalman filter, compared with a vision-based global reference localization system.

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“…With the fusion of multiple sensors i.e. two laser sensors and camera sensors a novel scheme for object localization and tracking was presented by researchers [2]. A hybrid RFID and computer vision system for fine-grained localization and tracking of tagged objects called as TagVision along with a fusion algorithm was suggested to organically combine the position information given by the CV subsystem, and phase data output by the RFID subsystem [3].The problem of tracking dynamic objects with UHF RFID tags using a Bayesian framework with a mobile robot was addressed.…”

Section: Imentioning

confidence: 99%

Stem – An Iot Based Solution For Tracking Objects

Prasad¹

2017

IJRASET

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Internet Of things (IoT) is an inter-connected networking ecosystem of physical objects also called as "things" embedded with softwares, sensors, electronics provided with unique IP addresses which are accessible through internet and are capable of collecting and sharing data in a network without the intervention of humans. In this journal the author proposes a neural network guided model to track and find real-time updates of objects which will be tracked and updated bythe means of Radio Frequency identification (RFID). This will help corporate resources to be handled in an effective way. In order to assist and smoothen the process of tracking and precisely locating any physical object amongst corporate and professional environment through IoT is our idea. We propose a model called as Sensor based Tracking Enabled Model (STEM) deals with various processes in order to correctly identify, track and locate the essentials and objects used in professional environment Keywords: IOT,RFID,Objecttracking,realtime,sensorsthe help of this advancing technology, any physical object can be connected to internet which can be tagged and precise location of that object can be tracked and the data can also be used for further processing and analysis due to which it is known as Internet Of Things. In this so-called busy world where time is a constraint, we often battle with ourselves for very small fundamental crucial needs such as finding or locating our own essential belongings and stuffs . I.IOT AND RFID The accurate tracking of real time indoor objects based upon the aggregated binary measurements implemented by particle filtering was proposed which were tagged in Ultra High Frequency (UHF) Radio Frequency Identification (RFID) systems [1]. With the fusion of multiple sensors i.e. two laser sensors and camera sensors a novel scheme for object localization and tracking was presented by researchers [2]. A hybrid RFID and computer vision system for fine-grained localization and tracking of tagged objects called as TagVision along with a fusion algorithm was suggested to organically combine the position information given by the CV subsystem, and phase data output by the RFID subsystem [3].The problem of tracking dynamic objects with UHF RFID tags using a Bayesian framework with a mobile robot was addressed. The two stage dynamic motion model was combined with the dual particle filter in order to capture the dynamic motion of the object and to quickly recover from failures in tracking. And this approach was then tested on a Scitos G5 mobile robot through various experiments [4]. The researchers proposed a novel ubiquitous architecture followed by a protocol for tracking mobile objects in real-time based upon the RFID Tags [5] .An internet based concept incorporated with RFID technology was proposed to form an internet based application for the library management and the RFID reader Motorola MC9090 was used for the entire process which was carried inside the library [6]. The way of finding and navigating to an object with...

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Object localization and tracking based on multiple sensor fusion in intelligent home

Cited by 3 publications

References 9 publications

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Divergent trinocular vision observers design for extended Kalman filter robot state estimation

Stem – An Iot Based Solution For Tracking Objects

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