Review of UAV positioning in indoor environments and new proposal based on US measurements

Este documento se considera que es una ponencia de congresos en lugar de un capítulo de libro.10th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2019) Pisa, Italy, September 30th - October 3rd, 2019The use of unmanned aerial vehicles (UAVs) has increased dramatically in recent years because of their huge potential in both civil and military applications and the decrease in prize of UAVs products. Location detection can be implemented through GNSS technology in outdoor environments, nevertheless its accuracy could be insufficient for some applications. Usability of GNSS in indoor environments is limited due to the signal attenuation as it cross through walls or the absence of line of sight. Considering the big market opportunity of indoor UAVs many researchers are devoting their efforts in the exploration of solutions for their positioning. Indoor UAV applications include location based services (LBS), advertisement, ambient assisted living environments or emergency response. This work is an update survey in UAV indoor localization, so it can provide a guide and technical comparison perspective of different technologies with their main advantages and drawbacks. Finally, we propose an approach based on an ultrasonic local positioning system.Universidad de AlcaláJunta de Comunidades de Castilla-La ManchaMinisterio de Economía, Industria y Competitivida

Localização para Smart Devices tirando partido de iBeacons

A massificacao dos dispositivos de localização por satélite popularizou este tema, que hoje em dia se encontra amplamente experimentado e testado. Por outro lado, a evolução dos dispositivos móveis traz novas tecnologias e funcionalidades. O Bluetooth v4.0 é uma delas. Os iBeacons contém esta tecnologia e com base nas vantagens que traz, como o baixo custo e o baixo consumo, foi desenvolvido um sistema de localização baseado no RSSI. Este sistema é composto por dispositivos móveis, como os telemóveis de última geraçao, com o Sistema Operativo Android e uma aplicação criada para o efeito da localizaçao e os iBeacons como pontos de referênciaThe massification of devices based on satellite localization popularized this theme, which is widely well-tried and tested nowadays. On the other hand, the evolution of mobile devices brings new technologies and features. Bluetooth v4.0 is one of them. The iBeacons contains this technology and based on the advantages it brings, such as low cost, low consumption, a tracking system was developed. This system will be composed of mobile devices such as latest generation mobile phones, with the Android operating system and an application created for the purpose of location and iBeacons as reference point

Improving Indoor BlueTooth Localization By Using Bayesian Reasoning To Explore System Parameters

With the advent of smaller, more mobile electronic devices, a wide variety of services can now be augmented with the additional context that is provided by positional information. Systems commonly used for outdoor localization, such as GPS, cannot necessarily be used for indoor localization because often, separating a localizing device from system infrastructure with walls and other obstacles lowers accuracy. Instead, indoor localization systems can be deployed to replace the contextual information required for some situated services, that would otherwise be lost when a device moves indoors. For example, the trilateration algorithm that GPS uses to combine distance estimates from satellites can be repeated using Bluetooth (BT) devices spread throughout an environment. The signal strength of a set of beacons can be read by a localizing device, and those signal strengths can be equated to the distance between the localizing device and the beacon. These distances can then be combined using trilateration. A major source of error in such a system is that BT signal strength does not map directly to only one distance. Because microwave frequency propagation is susceptible to multipath effects and antenna direction, two devices at a fixed location can read a variety of signal strengths, which may not map to the ideal line-of-sight calibrated value. Therefore, any given signal strength reading cannot be interpreted as a single distance without introducing the potential for substantial error. One solution is to probabilistically model the relationship between distance and signal strength by modelling BT localization using a Bayesian network. In a Bayesian network, the distance versus signal strength relationship is stored as the conditional probability of a signal strength reading given a specific distance. Using a Bayesian inference algorithm, one can then reason backwards from a signal strength to a probability distribution representing the estimated position of the localizing BT device. In this thesis, I explore some of the effects of modelling BT localization with a Bayesian network. I first extend the probabilistic calibration to include the influence of the relative orientation of device antennae on the attenuation of BT signal strength between them. I then experiment with the effects of the position of a receiver within a discrete spatial bin, and of the proximity of the transmitters to the edges of the discrete space, because both have the potential to reduce the accuracy of localization using discrete variables. I found that neither affected the localization results in a significant, avoidable fashion. I then studied the effects of the scope of calibration, in terms of the number of distance values used, and of the number of beacons used in localization. I found that additional distance values and a smaller minimum distance used in calibration could result in increased BT localization accuracy, whereas many BT localization systems perform little calibration at distances smaller than 2 m. I also found that accuracy increased when the number of beacons was greater than four, and that accuracy did not significantly decrease when the number of beacons was three or fewer; whereas most trilateration systems use only three or four beacons. I conclude in general that a combination of probabilistic trilateration calibration and Bayesian network inference are viable techniques, and could allow for improvements to localization accuracy in a number of areas

Evaluation and Comparison of Ultrasonic and UWB Technology for Indoor Localization in an Industrial Environment

Evaluations of different technologies and solutions for indoor localization exist but only a few are aimed at the industrial context. In this paper, we compare and analyze two prominent solutions based on Ultra Wide Band Radio (Pozyx) and Ultrasound (GoT), both installed in an industrial manufacturing laboratory. The comparison comprises a static and a dynamic case. The static case evaluates average localization errors over 90 s intervals for 100 ground-truth points at three different heights, corresponding to different relevant objects in an industrial environment: mobile robots, pallets, forklifts and worker helmets. The average error obtained across the laboratory is similar for both systems and is between 0.3 m and 0.6 m, with higher errors for low altitudes. The dynamic case is performed with a mobile robot travelling with an average speed of 0.5 m/s at a height of 0.3 m. In this case, low frequency error components are filtered out to focus the comparison on dynamic errors. Average dynamic errors are within 0.3–0.4 m for Pozyx and within 0.1–0.2 m for GoT. Results show an acceptable accuracy required for tracking people or objects and could serve as a guideline for the least achievable accuracy when applied for mobile robotics in conjunction with other elements of a robotic navigation stack