By enabling coordinated task execution and movement, robotic swarms can achieve efficient exploration or disaster site management. When utilizing Ultra-wideband (UWB) radio technology for ranging, the proposed relative localization sensor can be made lightweight and relatively indifferent to the ambient environment. Infrastructure dependency is eliminated by making the whole sensor fit on a swarm agent, while allowing for a certain amount of positional error. In this thesis, a novel algorithm is implemented in to constrained hardware and compared to a more traditional trilateration approach. Both algorithms utilize Particle Swarm Optimization (PSO) to be more robust towards noise and achieves similar accuracy, but the proposed algorithm can run up to ten times faster. The antenna array which forms the localization sensor weighs only 56g, and achieves around 0.5m RMSE with a 10Hz update rate. Experiments show that the accuracy can be further improved if the rotational bias observed in the UWB devices are compensated for.

Motion capture technology has been applied in many fields such as animation, medicine, military, etc. since it was first proposed in the 1970s. Based on the principles applied, motion capture technology is generally classified into six categories: 1) Optical; 2) Inertial; 3) Magnetic; 4) Mechanical; 5) Acoustic and 6) Markerless. Different from the other five kinds of motion capture technologies which try to track path of specific points with different equipment, markerless systems recognize human or non-human body's motion with vision-based technology which focuses on analyzing and processing the captured images for motion capture. The user doed not need to wear any equipment and is free to do any action in an extensible measurement area while a markerless motion capture system is working. Though this kind of system is considered as the preferred solution for motion capture, the difficulty for realizing an effective and high accuracy markerless system is much higher than the other technologies mentioned, which makes markerless motion capture development a popular research direction. Microsoft Kinect sensor has attracted lots of attention since the launch of its first version with its depth sensing feature which gives the sensor the ability to do motion capture without any extra devices. Recently, Microsoft released a new version of Kinect sensor with improved hardware and and targeted at the consumer market. However, to the best of our knowlege, the accuracy assessment of the sensor remains to be answered since it was released. In this thesis, we measure the depth accuracy of the newly released Kinect v2 depth sensor from different aspects and propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. Based on the trilateration method, a low-cost, no wearable equipment requirement and easy setup human gait tracking system is realized.

The use of smartphones for positioning and navigation is mostly limited to outdoor settings. Indoors, where GPS signals are too inaccurate for positioning, an alternative must be used. This project aimed at producing an indoor positioning system which could be both configured and used by an end user organization without equipping its buildings with proprietary hardware. The prerequisites were that a complete digital representation of the building floors is available, and that the floors have a sufficient amount of WiFi access points. Our system measures radio signal strength from existing WiFi infrastructure using a smartphone. This data is sent to a backend and is used to position a device using two different methods: trilateration and fingerprinting. The finished system can position a user with an accuracy of approximately four meters using fingerprinting instead of trilateration as it yielded the best results. The building used for testing was scanned using a smartphone equipped with our application, something that we would expect an end user to be able to do. / Användandet av smartphones för positionering och navigering är mestadels inriktat på utomhusanvändning. Inomhus är GPS signaler inte tillräckligt noggranna för positionering, och ett alternativ måste användas. Det här projektets mål var att producera ett inomhuspositioneringssystem som kan konfigureras och användas av slutanvändarorganisationen utan att behöva utrusta sina byggnader med proprietär hårdvara. Förutsättningarna är att en komplett digital representation av byggnaden finns tillgänglig, och att våningsplanen har tillräckligt många WiFi basstationer. Vårt system mäter radiosignalstyrka från den existerande WiFi infrastrukturen. Denna data skickas till en backend och används i två olika metoder: trilateration och fingerprinting. Det slutgiltiga systemet kan positionera en användare med en träffsäkerhet på ungefär fyra meter när fingerprintingmetoden används då den producerade det bästa resultatet. Byggnaden som systemet testades i skannades av en smartphone med vår applikation, en sak som vi förväntar oss att en slutanvändare skulle kunna göra själv.

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Theme of the thesis is research and possibility of using GPS system from localization in wireless sensor network. Paper deals with the accuracy and energy consumption of GPS localization. Thesis also solve using of localization in local anchor system. Theoretical part describes IEEE 802.15.4 standard, capability of used nodes and describe ways how to use RSSI value to resolve location

The main theme of this thesis are problems of locating of wireless units in localization systems represented by wireless sensor networks. The thesis describes principle of trilateration and Levenberg-Marquardt algorithm. The main theme of this thesis is simulation of behavior of localisation systems and possible optimization of localization.

The master thesis is concerned with problem of localization of nodes in wireless sensor network WSN implemented by ZigBee technology. The thesis provide description of ZigBee architecture involving signal description. The method of evaluating coordinates basically do not depend on used measuring methods. The method  of fingerprinting is included in separated category based on only statistical processing of RSSI data. Determination of coordinates of mobile node always needs finding out range, signal time of arrival (ToA) or angle of arrival (AoA) in respect to anchors node given dimension magnitude. The author found out three possible solutions for range measuring and one solution for angle of arrival measuring useable in context of ZigBee wireless sensor network. Finally the author discuss possibilities and constraints of ZigBee network with used measuring type.

This thesis explores the possibilities of constructing an indoor positioning system based on Bluetooth Smart technology. Two non-trainable trilateration approaches and two trainable fingerprinting were implemented and evaluated at Mobiento's offices in Stockholm, Sweden. A trilateration approach is based on finding a sought location based on known distances towards know locations, at least three locations and distances are needed. A fingerprinting approach is based on creating a radio map, which describes transmission signals within the room, towards different transmitters. A set amount of coordinates are assigned a fingerprint. These are then used as reference points for a sought location. For each major approach, trilateration and fingerprinting, a weighted approach is conducted. These approaches are evaluated in a disturbance free environment in term of accuracy, implementation and setup. In terms of accuracy, the non-weighted fingerprinting approach performs slightly better than the weighted fingerprinting approaches. Both of these are more accurate than the trilateration approaches. When it comes to implementation and setup, the trilateration algorithms impose less cost. These allow for better scalability when the indoor environment becomes larger.

Internet of Things ger människor möjligheter att genom tjänster dra nytta av sensorer och andra enheter som tillsammans skapar ett brett utbud av lösningar som smart hem, smart transport, äldreomsorg och mycket mer. Den senaste innovationen av Bluetooth SIG är Bluetooth mesh topologi som tillåter att ansluta trådlösa enheter i ett många till många förhållanden. I denna avhandling utvecklade vi ett inomhusspårningssystem baserat på Bluetooth Low Energy teknik och mesh topologi för att undersöka de potentiella fördelar som Bluetooth Low Energy nätverk har att erbjuda för inomhusspårningssystemet. Systemet är utvecklat för att spåra Bluetooth beacon i en inomhus kontorsmiljö. Received Signal Strength används för att beräkna avståndet till beacon, medan positionen av beacon beräknas med Extended Min-Max och Trilateration algoritmer. Beräkningar utförs på servern. Resultaten analyseras genom jämförelse av Root Mean Square Error av båda algoritmerna. I denna avhandling utvärderas inomhusspårning som en del av ett uppdrag som ges av u-blox. / The Internet of Things brings connectivity of people, services, sensors and other devicesenabling a wide range of applications like smart home, smart transport, elder care andmuch more. The latest innovation of Bluetooth SIG is the Bluetooth mesh topology thatallows us to connect wireless devices in a many-to-many relationship. To investigate thepotential benefit that the BLE mesh network has to offer for the indoor tracking system.In this thesis, we developed an indoor tracking system based on Bluetooth Low Energytechnology and mesh topology. The system is developed to track Bluetooth beacon inan indoor office environment. Received Signal Strength is used to calculate the distance tothe beacon, while the position of the beacon is calculated using Extended Min-Max andTrilateration algorithms. Calculations are performed on the server. The results are analysed through comparison of Root Mean Square Error of both algorithms. In this thesis, indoor tracking is evaluated as part of an assignment given by u-blox.

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