WiFi-based indoor positioning

Yang, Chouchang; Shao, Huai-Rong

doi:10.1109/mcom.2015.7060497

Cited by 618 publications

(269 citation statements)

References 16 publications

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“…For example, in [2] a WiFi-based approach is described. Simulations show that this positioning system can achieve around 1 m accuracy without any hardware change in commercial WiFi products but relying on wide signal bandwidth and large numbers of antennas by utilizing the transmission of multiple predefined messages .…”

Section: A Indoor Localization Systemsmentioning

confidence: 99%

WiFi ad-hoc mesh network and MAC protocol solution for UWB indoor localization systems

Ridolfi

Velde

Steendam

et al. 2016

2016 Symposium on Communications and Vehicular Technologies (SCVT)

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Abstract-Ultra-wideband (UWB) is an emerging technology that is well known for its capability to provide centimeter positioning precision which is essential for applications that require very high accuracy. However, although several accuracy improving algorithms have been proposed in scientific literature, solutions to improve the scalability (in terms of coverage and dense user deployments) have not been explored yet or are still under examination. To this end, this paper presents a WiFi-UWB solution in which the UWB indoor localization system is deployed on top of a WiFi ad-hoc mesh network. The combination of a high-throughput WiFi mesh backbone in combination with a high-accuracy UWB radios allows deployment in areas without existing (wired) backbones. Moreover, the possibility for the clients to move around the covered area maintaining fully connectivity (roaming feature) is implemented. Finally, to improve scalability, a Time Division Multiple Access (TDMA) MAC protocol that combines WiFi and UWB technologies is proposed, thereby improving the scalability of the network towards multiple mobile users. As such, the solution combines the strengths of the WiFi technology (high throughput and efficient multi-hop meshing with roaming) with the main strengths of UWB (high accuracy localization). Overall the system supports 100 simultaneous clients while supporting multi-hop roaming with 150 ms delays.

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Section: A Indoor Localization Systemsmentioning

confidence: 99%

WiFi ad-hoc mesh network and MAC protocol solution for UWB indoor localization systems

Ridolfi

Velde

Steendam

et al. 2016

2016 Symposium on Communications and Vehicular Technologies (SCVT)

View full text Add to dashboard Cite

show abstract

“…There are various kinds of useful approaches, such as radio frequency identification (RFID) [1][2][3], ZigBee, WiFi [4][5][6][7], have been proved in many research studies over the past years. Recently, a robotics company (Marvelmind Robotics: Sunnyvale, CA, USA) has even launched an "Indoor GPS" with ±2 cm precision based on stationary ultrasonic beacons united by radio interface in a license-free band [8].…”

Section: Introductionmentioning

confidence: 99%

Indoor Autonomous Vehicle Navigation—A Feasibility Study Based on Infrared Technology

Run

Xiao

2018

ASI

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Abstract:The application of autonomous vehicles has grown dramatically in recent years. Not only has the rail-guided vehicle (RGV) been used widely in traditional production lines, the automatic guided vehicle (AGV) has also been increasingly used. Positioning and path planning are two major functions of autonomous vehicles; however, there are many ways to fulfill the above requirements. The infrared remote control has been heavily and successfully used in home appliances for decades, which has encouraged us to apply this mature and cost-effective technology to an autonomous vehicle. By decoding the coded signal from the infrared light-emitting diode (LED), which is equipped on the ceiling, the autonomous vehicle can be positioned with an accuracy of less than 50 mm. On the other hand, by changing the beam pattern of infrared light from the ceiling, an invisible route can be produced on the ground. That is to say, instead of the traditional rail-guided method, these invisible paths can guide the autonomous vehicle. We have implemented a prototype of an autonomous vehicle system based on the above concept, with the aim of creating a simple and reliable approach for the navigation of an indoor autonomous vehicle.

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“…These algorithms are mainly based on measuring the distances to access points by means of the angle of arrival (AOA), the time of arrival (TOA), the carrier phase of arrival (POA), or the received signal strength indicator (RSSI), and so forth [1,2]. With the increase of WiFi access points deployed in public areas, researchers have put focus on Wi-Fi-based indoor localization [3][4][5]. However, the localization system based on Wi-Fi signals usually cannot provide users with stable results because moving objects or persons affect the signal strength.…”

Section: Introductionmentioning

confidence: 99%

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

Feng

Tan

2017

Journal of Sensors

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RGB-D sensors capture RGB images and depth images simultaneously, which makes it possible to acquire the depth information at pixel level. This paper focuses on the use of RGB-D sensors to construct a visual map which is an extended dense 3D map containing essential elements for image-based localization, such as poses of the database camera, visual features, and 3D structures of the building. Taking advantage of matched visual features and corresponding depth values, a novel local optimization algorithm is proposed to achieve point cloud registration and database camera pose estimation. Next, graph-based optimization is used to obtain the global consistency of the map. On the basis of the visual map, the image-based localization method is investigated, making use of the epipolar constraint. The performance of the visual map construction and the image-based localization are evaluated on typical indoor scenes. The simulation results show that the average position errors of the database camera and the query camera can be limited to within 0.2 meters and 0.9 meters, respectively.

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WiFi-based indoor positioning

Cited by 618 publications

References 16 publications

WiFi ad-hoc mesh network and MAC protocol solution for UWB indoor localization systems

WiFi ad-hoc mesh network and MAC protocol solution for UWB indoor localization systems

Indoor Autonomous Vehicle Navigation—A Feasibility Study Based on Infrared Technology

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

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