This report documents the development of the Subwave, a remotely-operated underwater vehicle (ROV), and an artificial neural network based inertial positioning system. The Subwave uses the open-source ArduSub software framework, commercial-off-the-shelf hardware components, and several custom systems. It is designed as a platform for researching autonomous underwater vehicles (AUVs). The first step for an AUV is navigating waypoints, which requires the AUV to know its global position. Since global navigation satellite systems (GNSSs) are denied underwater, the available underwater positioning systems were surveyed and determined that all the available systems were too large and expensive for the Subwave. It was also discovered that the only consistent underwater positioning method was inertial positioning. So, experimentation began on a small, low-cost system that employs an artificial neural network to predict latitude and longitude using micro-electromechanical system (MEMS) inertial measurement unit (IMU) data as inputs, which would become the Neural-Inertial Positioning System.

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Denna rapport sammanfattar resultat av ett examensarbete på en högskoleingenjörsutbildningsom utfördes av två studenter på Malmö högskola.Arbetets syfte var att genomföra en mängd olika experiment med accelerometer, barometeroch GPS i en modern smarttelefon. Ett antal scenarier för en tänkbar sensoranvändning i applikationerformulerades för att vägleda olika experiment. Experimentdata dokumenterades noggrantoch analyserades med avsikten att skapa en databank med information för framtida studier.Analys av data inkluderar höjdbestämning i naturen och i byggnader med hjälp av barometersensor,geografisk position med hjälp av GPS, hastighet och acceleration under en hissfärdmed hjälp av accelerometer.Rapporten innehåller en omfattande litteraturstudie om användning av sensorer vid inomhuspositionering.Från analys av mätdata, kom vi fram till slutsatsen att är möjligt att beräkna höjdenfrån barometerdata med bra noggrannhet under optimala omständigheter. GPS höjdenfrån mätningarna har stor felmarginal jämfört med den verkliga höjden samt när den jämförsmed den beräknade höjden från barometern.Genom att utföra en numerisk integration på accelerometer-data kom vi fram till att det är möjligtatt beräkna ungefär hur långt man har färdats med en hiss, dock att vissa detaljer måste tasi beaktning. / This report summarizes the results of a degree Bachelor of engineering in Computer Scienceconducted by two students at Malmo University.Work aim was to conduct a variety of experiments with accelerometer, barometer and GPS in amodern smartphone. A number of scenarios for a possible sensor use in applications formulatedto guided experiments. Data is carefully documented and analyzed, with the intention tocreate a database of information for future studies. Analysis of the data includes the altitudedetermination in nature and in buildings using barometric sensor, geographic location usingGPS, speed and acceleration during an elevator journey with the help of accelerometer.The report contains a comprehensive literature review on the use of sensors for indoorpositioning.From our analysis of the measurement data, we conclude that it is possible to calculate thealtitude from barometric- information but good accuracy if there are optimum circumstances.GPS altitude from our measurements show faulty height by a large margin compared with theactual height and when it is compared with the calculated height of the barometer the barometricheight is closer to the actual height.By performing a numerical integration of the accelerometer data, the results show that it ispossible to calculate approximately how far you have traveled in meters in an elevator, howeverthere are some things that must be taken into consideration.

Aim of this thesis is to search the market for suitable autonomous robot to be used by smart house. The research in this work is partly done on the range of abilities of smart houses in matter of sensor systems, ability of data processing and their use by mobile robots. The output of this thesis is robotics application written using Microsoft Robotics Developer Studio (C#) and simulated using Visual Simulation Environment. Main feature of this robotic application is the interface between robot and smart house, and robot and user. This interface enables employer to directly control robot's movement or to use automated pathfinding. The robot is able to navigate in dynamic environment and to register, interact and eventually forget temporary obstacles.