Global ETD Search

171	3D mapování s využitím řídkých dat senzoru LiDAR / 3D Mapping from Sparse LiDAR Data Veľas, Martin Unknown Date (has links) Tato práce se zabývá návrhem nových algoritmů pro zpracování řídkých 3D dat senzorů LiDAR, včetně kompletního návrhu batohovího mobilního mapovacího řešení. Tento výzkum byl motivován potřebou takových řešení v oblasti geodézie, mobilního průzkumu a výstavby. Nejprve je prezentován iterační algoritmus pro spolehlivou registraci mračen bodů a odhad odometrie z měření 3D LiDARu. Problém řídkosti a velikosti těchto dat je řešen pomocí náhodného vzorkování pomocí Collar Line Segments (CLS). Vyhodnocení na standardní datové sadě KITTI ukázalo vynikající přesnost oproti známému algoritmu General ICP. Konvoluční neuronové sítě hrají důležitou roli ve druhé metodě odhadu odometrie, která zpracovává kódovaná data LiDARu do 2D matic. Metoda je schopna online výkonu, zatímco je zachována přesnost, když požadujeme pouze parametry posunu. To může být užitečné v situacích, kdy je vyžadován online náhled mapování a parametry rotace mohou být spolehlivě poskytnuty např. senzorem IMU. Na základě algoritmu CLS bylo navrženo a implementováno batohové mobilní mapovací řešení 4RECON. S využitím kalibrovaného a synchronizovaného páru LiDARů Velodyne a s nasazením řešení GNSS/INS s duální anténou, byl vyvinut univerzální systém poskytující přesné 3D modelování malých vnitřních i velkých otevřených prostředí. Naše hodnocení prokázalo, že požadavky stanovené pro tento systém byly splněny -- relativní přesnost do $5$~cm a průměrná chyba georeferencí pod $12$~cm. Poslední stránky obsahují popis a vyhodnocení další metody založené na konvolučních neuronových sítích -- navržených pro segmentaci země v mračnech bodů 3D LiDARu. Tato metoda překonala současný stav techniky v této oblasti a představuje způsob, jakým může být sémantická informace vložena do 3D laserových dat.
172	Absolute and Relative Navigation of an sUAS Swarm Using Integrated GNSS, Inertial and Range Radios Huff, Joel E. January 2018 (has links) No description available. Electrical Engineering sUAS small unmanned aircraft systems range radio filter kalman navigation aviation relative navigation relative sensor fusion decawave IMU INS inertial GNSS GPS satellite swarm swarm navigation cooperative
173	Multiple Hypothesis Testing Approach to Pedestrian Inertial Navigation with Non-recursive Bayesian Map-matching Koroglu, Muhammed Taha 22 September 2020 (has links) No description available. Engineering Electrical Engineering pedestrian tracking MEMS inertial navigation system INS inertial measurement unit IMU building information model BIM map-matching multiple hypothesis testing Kalman Filter Particle Filter Bayesian Filtering pedestrian INS, zero velocity ZUPT
174	Development of a Digital Coaching Application with Automated Mistake Identification using a Multi-Sensor Configuration / Utveckling av en digital träningsapplikation med automatiserad felidentifiering med hjälp av en multisensorkonfiguration Chrysanthou, Andreas January 2023 (has links) Home-based exercise is a popular physical activity of maintaining fitness, health andwellness in general. However, without proper supervision and basic knowledge of theexercises in the workout plan, there is an increased risk of injury. Considering that noteveryone is willing to attend crowded gyms or schedule professional personal trainingsessions, in this study, a novel feedback system is proposed, in the form of a mobileapplication. Accelerometer and gyroscope data were collected from 10 volunteersperforming 3 exercises, squats, lunges and bridges, with inertial sensors attachedto their back lumbar region, on both shanks and on both thighs. Each participantperformed 5 repetitions of the correct technique and 5 repetitions of 4 mistakes foreach exercise. The accuracies of 3 classifiers, a SVM, a RF and DT were comparedwith the SVM performing the best across all 3 exercises. The best location and numberof sensors was determined by examining the accuracy of a SVM model for 15 uniquemulti-sensor configurations. The best performing setup, being the configuration with 2sensors, one at the lumbar area and one at the shank, was used in exploring the efficacyof different data processing techniques. Time-domain statistical features, sensor angletimeseries and the filtered signal timeseries were evaluated as input to a NN. The timedomainfeatures performed the best achieving the highest accuracy in all 3 exercises,with an accuracy of 67% for the squats, 87% for the lunges and 75% for the hip bridges.Overall, the final model demonstrated promising capabilities of classifying exercisetechnique of basic lower-body exercises, with a real-time feedback implementationbeing a feasible solution for self-efficient fitness. / Hemmaträning är en populär typ av fysisk aktivitet för att upprätthålla kondition,hälsa och välbefinnande. Dock utan övervakning och basal kunskap om hur olikaövningar bör utföras så finns det en ökad risk för skador. Alla människor går intefrivilligt till trånga och fullsatta gym eller bokar in pass med personlig tränare. Därförföreslås i denna studie ett nytt återkopplingssytem vid träning som kan användas via enmobilapp. Data från en accelerometer och ett gyroskop har samlats in från tio frivilligapersoner. De har utfört tre olika styrkeövningar; knäböj, utfallssteg och höftlyft medtröghetssensorer placerade på deras ländrygg, på underbenen och på låren. Varjedeltagare utförde fem repetitioner med korrekt teknik och sedan fem repetitionermed fyra olika typer av felaktig teknik för varje styrkeövning. Noggrannheten förtre klassificerare, SVM, RF och DT jämfördes sedan med det SVM som presteradebäst i alla tre styrkeövningarna. Det optimala antalet sensorer tillsammans med bästplacering av dessa räknades ut genom att undersöka en SVM modell med 15 unikamultisensorkonfigurationer. Det visade sig att kombinationen med två sensorer, envid ländryggen och en på underbenet var den bästa och därför användes den föratt undersöka effektiviteten av olika databehandlingstekniker. Tidsdomänsstatistiskafunktioner, sensorvinkeltidsserier och filtrerade signaltidsserier utvärderades sominmatning till ett NN. Tidsdomänsfunktionerna presterade bäst och uppnådde högstnoggrannhet i alla tre övningarna. Detta med ett korrekt utfall av 67% för knöböj,87% för utfallsteg och 75% för höftlyft. Sammantaget visade den slutliga modellenen lovande förmåga att klassificera träningsteknik för basala styrkeövningar för nedredelen av kroppen. Samtidigt som användaren får feedback i realtid vilket gör detmöjligt att utföra effektiv träning själv hemma. Sports technology wearable sensors multi-sensor IMU bodyweight exercise mobile application mHealth Idrottsteknologi bärbara sensorer multisensor kroppsviktsträning mobilapplikation mHälsa Sport and Fitness Sciences Idrottsvetenskap Other Computer and Information Science Annan data- och informationsvetenskap Signal Processing Signalbehandling
175	Methods and technologies for the analysis and interactive use of body movements in instrumental music performance Visi, Federico January 2017 (has links) A constantly growing corpus of interdisciplinary studies support the idea that music is a complex multimodal medium that is experienced not only by means of sounds but also through body movement. From this perspective, musical instruments can be seen as technological objects coupled with a repertoire of performance gestures. This repertoire is part of an ecological knowledge shared by musicians and listeners alike. It is part of the engine that guides musical experience and has a considerable expressive potential. This thesis explores technical and conceptual issues related to the analysis and creative use of music-related body movements in instrumental music performance. The complexity of this subject required an interdisciplinary approach, which includes the review of multiple theoretical accounts, quantitative and qualitative analysis of data collected in motion capture laboratories, the development and implementation of technologies for the interpretation and interactive use of motion data, and the creation of short musical pieces that actively employ the movement of the performers as an expressive musical feature. The theoretical framework is informed by embodied and enactive accounts of music cognition as well as by systematic studies of music-related movement and expressive music performance. The assumption that the movements of a musician are part of a shared knowledge is empirically explored through an experiment aimed at analysing the motion capture data of a violinist performing a selection of short musical excerpts. A group of subjects with no prior experience playing the violin is then asked to mime a performance following the audio excerpts recorded by the violinist. Motion data is recorded, analysed, and compared with the expert’s data. This is done both quantitatively through data analysis xii as well as qualitatively by relating the motion data to other high-level features and structures of the musical excerpts. Solutions to issues regarding capturing and storing movement data and its use in real-time scenarios are proposed. For the interactive use of motion-sensing technologies in music performance, various wearable sensors have been employed, along with different approaches for mapping control data to sound synthesis and signal processing parameters. In particular, novel approaches for the extraction of meaningful features from raw sensor data and the use of machine learning techniques for mapping movement to live electronics are described. To complete the framework, an essential element of this research project is the com- position and performance of études that explore the creative use of body movement in instrumental music from a Practice-as-Research perspective. This works as a test bed for the proposed concepts and techniques. Mapping concepts and technologies are challenged in a scenario constrained by the use of musical instruments, and different mapping ap- proaches are implemented and compared. In addition, techniques for notating movement in the score, and the impact of interactive motion sensor systems in instrumental music practice from the performer’s perspective are discussed. Finally, the chapter concluding the part of the thesis dedicated to practical implementations describes a novel method for mapping movement data to sound synthesis. This technique is based on the analysis of multimodal motion data collected from multiple subjects and its design draws from the theoretical, analytical, and practical works described throughout the dissertation. Overall, the parts and the diverse approaches that constitute this thesis work in synergy, contributing to the ongoing discourses on the study of musical gestures and the design of interactive music systems from multiple angles. 784
176	A Data Requisition Treatment Instrument For Clinical Quantifiable Soft Tissue Manipulation Abhinaba Bhattacharjee (6640157) 26 April 2019 (has links) <div>Soft tissue manipulation is a widely used practice by manual therapists from a variety of healthcare disciplines to evaluate and treat neuromusculoskeletal impairments using mechanical stimulation either by hand massage or specially-designed tools. The practice of a specific approach of targeted pressure application using distinguished rigid mechanical tools to breakdown adhesions, scar tissues and improve range of motion for affected joints is called Instrument-Assisted Soft Tissue Manipulation (IASTM). The efficacy of IASTM has been demonstrated as a means to improve mobility of joints, reduce pain, enhance flexibility and restore function. However, unlike the techniques of ultrasound, traction, electrical stimulation, etc. the practice of IASTM doesn't involve any standard to objectively characterize massage with physical parameters. Thus, most IASTM treatments are subjective to practitioner or patient subjective feedback, which essentially addresses a need to quantify therapeutic massage or IASTM treatment with adequate treatment parameters to document, better analyze, compare and validate STM treatment as an established, state-of-the-art practice.</div><div><br></div><div>This thesis focuses on the development and implementation of Quantifiable Soft Tissue Manipulation (QSTM™) Technology by designing an ergonomic, portable and miniaturized wired localized pressure applicator medical device (Q1), for characterizing soft tissue manipulation. Dose-load response in terms of forces in Newtons; pitch angle of the device with respect to treatment plane; stroke frequency of massage measured within stipulated time of treatment; all in real-time has been captured to characterize a QSTM session. A QSTM PC software (Q-WARE©) featuring a Treatment Record System subjective to individual patients to save and retrieve treatment diagnostics and a real-time graphical visual monitoring system has been developed from scratch on WINDOWS platform to successfully implement the technology. This quantitative analysis of STM treatment without visual monitoring has demonstrated inter-reliability and intra-reliability inconsistencies by clinicians in STM force application. While improved consistency of treatment application has been found when using visual monitoring from the QSTM feedback system. This system has also discriminated variabilities in application of high, medium and low dose-loads and stroke frequency analysis during targeted treatment sessions.</div> Computer Engineering Biomechanical Engineering Biomedical Instrumentation Medical Devices Circuits and Systems Control Systems, Robotics and Automation Engineering Instrumentation QSTM IASTM Skin-Pitch Stroke Frequency Q-Ware Dose-Load Force Quantification Treatment Mode Time Series Approximation Discrete Gaussian Kernel Active Time Dead Time 3D Load Cell IMU Sensor Treatment Session Treatment Subsession Device Pause State Geo-Angles Real-Time Computation Post-Processing Computation
177	Design and Development of a Data Acquisition and Communication System for Point Absorber Tracking Kannan, Balakrishnan January 2021 (has links) The recent trend in generating energy from the waves has led to several advancements in the methods and the various research is conducted across the world, to study the behaviour of point absorbers on the waves. The point absorbers such as wave buoys are designed to move according to the waves and the generator that is mechanically coupled with the buoys, generate electricity. But these buoys can also be used for measuring important parameters like the force acting on it due to the incident waves and their movement can be tracked to study the effects on the buoy due to the incident waves. This project, as an extension of a previous work titled ‘Design and Development of a Measurement System to Track the Motion of a Point Absorber’ by Juliana Lüer, focuses on modifying and replacing the controller data acquisition and the communication system. The main aim is to increase the stability of the system and increasing the size of data storage and range of the data transmission. This is done in 3 steps that are as follows: - The Arduino based controller is replaced with an advanced Raspberry Pi based computer called RevPi Compact. - The Secure Digital (SD) card storage is replaced with a solid-state (Universal Serial Bus) USB memory stick with a large capacity. - The Radio Frequency (RF) based data transmission is replaced with a 4G (fourth generation) internet modem. The 60 W solar panels are retained from the previous project. But the Lead-Acid battery is replaced with two Lithium Polymer (Li-Po) batteries of 768 Wh capacity each. This increases the stability of the power source and enables the buoy to stay active for a longer time even when there is no useful solar irradiance for many days. There are two force transducers (strain gauge) to measure the line force and the angular force acting on the buoy. The Ellipse2-D Inertial Measurement Unit (IMU) from SBG systems is retained from the previous experiment. This sensor can track the Altitude and Heading Reference (AHRS) data along with the Global Positioning System (GPS) data with high levels of accuracy. All the data collected are can be tracked instantaneously due to the 4G internet communication protocol and this is enabled by TelenorTM connection and HuaweiTM 4G modem. A copy of these data is also stored in a SanDisk USB memory of 500 GB capacity. The tests are carried out under the laboratory conditions and the outputs are as expected. The whole setup is to be installed in a metallic buoy and to be tested in the Lysekil test site in the future. Data Acquisition System Raspberry Pi Controller Processor Wave buoy Lysekil wave energy measurements IMU GPS Strain gauge force Solar energy Battery communication 4G internet Remote tracking Shell Python Energy Engineering Energiteknik Marine Engineering Marin teknik Annan elektroteknik och elektronik Elektroteknik och elektronik
178	Platform development of body area network for gait symmetry analysis using IMU and UWB technology Persson, Anders January 2018 (has links) Having a device with the capability of measure motions from gait produced by a human being, could be of most importance in medicine and sports. Physicians or researchers could measure and analyse key features of a person's gait for the purpose of rehabilitation or science, regarding neurological disabilities. Also in sports, professionals and hobbyists could use such a device for improving their technique or prevent injuries when performing. In this master thesis, I present the research of what technology is capable of today, regarding gait analysis devices. The research that was done has then help the development of a suggested standalone hardware sensor node for a Body Area Network, that can support research in gait analysis. Furthermore, several algorithms like for instance UWB Real-Time Location and Dead Reckoning IMU/AHRS algorithms, have been implemented and tested for the purpose of measuring motions and be able to run on the sensor node device. The work in this thesis shows that a IMU sensor have great potentials for generating high rate motion data while performing on a small mobile device. The UWB technology on the other hand, indicates a disappointment in performance regarding the intended application but can still be useful for wireless communication between sensor nodes. The report also points out the importance of using a high performance micro controller for achieving high accuracy in measurements. BAN Body Area Network gait gait symmetry gait symmetry analysis IMU inertial measurement unit UWB Ultra Wide-Band sensor node sensors sensor fusion electronics hardware Engineering and Technology Teknik och teknologier Elektroteknik och elektronik Embedded Systems Inbäddad systemteknik Communication Systems Kommunikationssystem Robotics Robotteknik och automation Signal Processing Signalbehandling Computer Systems Datorsystem Annan elektroteknik och elektronik Medicinsk laboratorie- och mätteknik Medical Equipment Engineering Medicinsk apparatteknik
179	Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms Vestin, Albin, Strandberg, Gustav January 2019 (has links) Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms. evaluation target tracking multiple sensors non-causal smoother smoothing tracking vehicle tracking camera lidar estimate estimation prediction vehicle dynamics sensor fusion real-time tracking extended kalman filter filter validation validation position estimation velocity estimation dynamic model model complexity multi object tracking multiple object tracking single object tracking data association tracking fundamentals iterated kalman filter track management gnn global nearest neighbour mahalanobis mahalanobis distance performance evaluation differential gps dgps roi ego several sensors sensors rmse root mean square error invertible motion anti-causal motion anti-causal tracking constant velocity gnn imu tfs two filter smoother ekf rts radar inertial measurement unit nonlinear nonlinear systems mono camera monocular camera noise model tracking performance fixed interval smoothing m/n logic centralized fusion non-causal object tracker car tracking car dynamics automotive active safety object tracking automotive industry thesis master reverse dynamics reverse tracking reverse sequence sequence tracking data propagation ground truth estimating ground truth additional sensors mounted sensors true estimates environment comparison algorithm independent targets overlapping measurements occluded track switch improve lower uncertainty more certain state process noise covariance sampling image sprt adas cnn cv pdf track target ego tracker tentative track observatiom online tracking offline tracking online offline recorded sequences robust self driving self-driving car traffic trajectory true state scenario scenarios future accurate output advanced driver assistance systems non-linear complex noise pedestrian truck bus maneuvering vehicles processed measurement frame state correction probability density function tuning likelihood transition measurement motion model recursion gaussian approximation distribution linear jacobian multiplicative noise ratio ad hoc ad hoc state space approach backward auction euclidean distance statistical threshold gating association margin normalize covariance matrix fusion confirmed rejected tentative history absolute error modular ego motion parameters variables logg hardware specification fused causal factorization independent uncorrelated transform moving rotation translation oncoming overtaking Control Engineering Reglerteknik

Search results