The Global Positioning System (GPS) and an Inertial Navigation System (INS)are two basic navigation systems. Due to their complementary characters in manyaspects, a GPS/INS integrated navigation system has been a hot research topic inthe recent decade. Both advantages and disadvantages of each individual systemare analyzed. The Micro Electrical Mechanical Sensors (MEMS) successfully solved theproblems of price, size and weight with the traditional INS. Therefore they arecommonly applied in GPS/INS integrated systems. The biggest problem ofMEMS is the large sensor errors, which rapidly degrade the navigationperformance in an exponential speed. By means of different methods, i.e.autoregressive model, Gauss-Markov process, Power Spectral Density and AllanVariance, we analyze the stochastic errors within the MEMS sensors. Real testson a MEMS based inertial measurement unit for each method are carried out. Theresults show that different methods give similar estimates of stochastic errorsources. These error coefficients can be used further in the Kalman filter for betternavigation performance and in the Doppler frequency estimate for fasteracquisition after the GPS signal outage. Three levels of GPS/IMU integration structures, i.e. loose, tight and ultra tightGPS/IMU navigation, are introduced with a brief analysis of each character. Theloose integration principles are given with detailed equations as well as the basicINS navigation principles. The Extended Kalman Filter (EKF) is introduced as the basic data fusionalgorithm, which is also the core of the whole navigation system to be presented.The kinematic constraints of land vehicle navigation, i.e. velocity constraint andheight constraint, are presented. These physical constraints can be used asadditional information to further reduce the navigation errors. The theoreticalanalysis of the Kalman filter with constraints are given to show the improvementon the navigation performance. As for the outliers in practical applications, theequivalent weight is introduced to adaptively reduce the influence on positioningaccuracy. A detailed implementation process of the GPS/IMU integration system is given.Based on the system model, we show the propagation of position standard errorswith the tight integration structure under different scenarios. Even less than 4observable satellites can contribute to the integrated system. Especially 2 satellitescan maintain the orientation errors at a reasonable level due to the benefit of thetight integration. A real test with loose integration structure is carried out, and theEKF performance as well as the physical constraints are analyzed in detail. Also atest with random outliers at the resolution level is carried out to show theeffectiveness of the equivalent weight. Finally some suggestions on future researchare proposed. / <p>QC 20111006</p>

Engaging in the music set of one’s favorite artist or DJ is oftentimes leading to the result of a powerful and euphoric felt experience, a sensation partly also induced from dancing in beat to the music. In an attempt to simulate a similar dance experience, a user-study was designed in order to investigate when a user is let to dance in rhythm to a music playback and in addition, in control of a music playback tempo through the induced dance movements. A proof-of-concept prototype was built and tested in an initial study, followed by a main study where the prototype had been modified and 12 participants participated. A questionnaire was given containing various question statements to be rated through a Likert-scale regarding their subjective experience. Open-ended questions were also included to collect their own opinions. From the results, an enhanced engagement and enjoyment of the music could be identified when being able to manipulate the tempo. / Att engagera sig i ett musikset av ens favoritartist eller DJ leder ofta till resultatet av en kraftfull och euforisk känsloupplevelse, en känsla delvis framkallat av att man dansar i takt med musiken. I ett försök att simulera en liknande dansupplevelse undersöker denna användarstudie när en användare dansar i rytm till musik och dessutom är i kontroll av tempot genom de skapade dansrörelserna. En proof-of-concept prototyp konstruerades och testades i en första studie, följt av en huvudstudie där prototypen hade modifierats och 12 deltagare deltog. Ett frågeformulär gavs med olika frågor som skulle bedömas via en Likert-skala, med avseende på deras subjektiva erfarenhet. Öppna frågor ingick också för att samla deras egna åsikter. Från resultaten kunde ett ökat engagemang och en förhöjd njutning av musiken identifieras när man kunde manipulera tempot.

Work-related musculoskeletal disorders constitutes a substantial burden for society, generating individual suffering and financial costs. Quantifying the musculoskeletal stress and establishing exposure-response relationships is an important step in facing this problem. Observational methods for assessing exposure in the field of ergonomics have shown poor results, and the technical measurement methods that exists are often complicated to use which limits their scope to scientific purposes. This work describes the development of a prototype measurement system aimed to simplify ambulatory measurements of musculoskeletal load, specifically aimed at the wrist and hand. Wearable sensors including Inertial Measurement Units (IMU:s) and Electromyography (EMG) were connected to a smartphone and used for measuring wrist movement and forearm muscle activity. Data sampled in the smartphone was stored online in a cloud database, and a webapplication was developed to visualize work-load exposure. Testing under controlled conditions indicated that muscular rest can be measured and classified according to suggested risk thresholds. Accurate angular measurements were difficult to implement because of lacking inter-sensor alignment in the horizontal plane, as well as uncertainties in the Bluetooth protocol. Future work should focus on the IMU:s and look to further develop a method of correcting the relative angle error, as well as investigating accurate time synchronization of the two sensors.Alternatively, deriving angular velocities directly from the IMU gyroscopes could be investigated.

This work focuses on the influence of terror, extremism, trafficking and corruption on the regional security of Central Asia, with a particular emphasis on Kazakhstan. Kazakhstan is regarded as the most stable and financially developed state in Central Asia, yet domestic and regional stability are threatened by the rise in extremism, narcotics trafficking, institutional corruption and acts of terrorism. The challenges of trafficking and extremism within the region originated from outside of Central Asia. Foreign organizations and ideologies are significant actors in progression of regional instability. Government response to these challenges can perpetuate or stymie the aforementioned threats to regional security. Repressive regimes inadvertently contribute to the propaganda of the non-state foes. A prominent solution is the international program referred to as border management. This program aims to support border security while also promoting economic growth and ensuring the protection of human rights. Improved borders promotes regional security, economic growth can potentially undermine the growth of corruption and human rights protection can undermine a large part of extremist propaganda.

No description available.

One of the causes of work-related Musculoskeletal Disorders (MSDs) is the manual handling of heavy objects. To reduce the risk of such injuries, workers are instructed to follow general guidelines on how to lift and carry objects depending on their mass. Current ergonomic assessments using wearable sensors can differentiate correct from incorrect body postures but are limited. Being able to estimate the mass of an object during ergonomic assessment would be a great improvement. This work investigates a combination of Inertial Measurement Units (IMUs) and Electromyography (EMG) sensors for offline estimation of an object’s mass for different movements. 10 participants performed 26 lifting and carrying trials with loads from 0 to 19 kg, while wearing a 17IMU motion capture system and EMG sensors on both biceps brachii and both erector spinae. Two methods were considered to estimate the carried mass: (1) supervised machine learning and (2) musculoskeletal modeling. First, the data was used to select features, train, and compare regression models. The lowest Mean Squared Error (MSE) for 10-fold cross-validation for lifting and carrying combined was 5.8113 for a Gaussian Process Regression (GPR) model with an exponential kernel function. Then, a MSE of 4.42 and a Mean Absolute Error (MAE) of 1.63 kg were obtained also with a GPR for Leave-One-Subject-Out Cross-Validation (LOSOCV) only for lifting and frontal carrying trials. For the same trials, the upper-extremity musculoskeletal model, scaled to each participant, estimated the mass with a MSE of 1.78 and a MAE of 0.95 kg. The study was restricted to lifting and frontal carrying, but the combination of the two technologies showed great potential for object mass estimation.

There is a need for objective methods for wrist angular velocity measurements for accurate risk assessments because there is a high frequency of musculoskeletal disorder in workers. The goal of this project was to validate the accuracy of inertial measurement unit sensors to measure the angular velocity. More specifically, the purpose of this master thesis project was to apply an alternative algorithm to compute the markers velocity, other than the one from the optical system that Jenny Wingqvist, and Josephine Lantz used. The project used an experimental data of 10 participants from the previous project done by Jenny Wingqvist and Josephine Lantz. To validate the accuracy, the data of angular velocity of the sensors was compared with the data of angular velocity of markers. The lowest mean value of the root mean square differences value was 23.5 degrees/s during flexion and deviation standard movements at 40 BPM (Beats Per Minute) and the maximum value was 110.5 degrees/s at 140 BPM. The mean value of the correlation coefficients between markers and sensors angular velocities in standard movements of flexion and deviation were 0.85, 0.88, and 0.89 at 40 BPM, 90 BPM, and 140 BPM, respectively. The smallest and the largest mean value of the absolute difference in 50th percentile was found in 40 BPM (19.4±11.3), and 140 BPM (51.2±28.5) respectively. The decorrelation coefficient between the subjects 50th percentile of the angular velocity was 0.91 for the standard movements. The upper limit of agreement for the standard movements was 78.36 degrees/s, while the lower limit of agreement was -13.76 degrees/s.  The results show that the error was too large, so there is a need of further research to measure the wrist angular velocity using IMU sensors.

Road roughness is the primary source of vehicle vibrations. This thesis investigates model-based methods for estimating road roughness in terms of the International Roughness Index (IRI) by measuring the chassis vibrations of the vehicle. This can provide NIRA Dynamics AB with a cost-effective pavement monitoring solution. Initially, system identification is performed on a physical car to estimate model parameters that reflect reality. Subsequently, two model-based IRI estimation methods are developed. One method relies on a transfer function between vertical chassis vibrations and the IRI according to a quarter-car model. The second method aims first to estimate the longitudinal road profile using a Kalman filter, and then calculate the IRI values from the estimated profile. This method can be implemented computationally efficiently and also offers the possibility of estimating the IRI using lateral vibrations. Both methods are validated using real-world data, and their performance is similar when using vertical vibrations, with the IRI estimation error’s standard deviation being roughly 10% to 20% of the reference value. However, the results are considerably worse when the estimation is purely based on lateral vibrations, indicating that lateral vibrations are not feasible for model-based IRI estimation, and the reasons for this are discussed.

This thesis presents a framework for a hybrid model-free marker-less inertial-visual camera pose tracking with an integrated sensor fusion mechanism. The proposed solution addresses the fundamental problem of pose recovery in computer vision and robotics and provides an improved solution for wide-area pose tracking that can be used on mobile platforms and in real-time applications. In order to arrive at a suitable pose tracking algorithm, an in-depth investigation was conducted into current methods and sensors used for pose tracking. Preliminary experiments were then carried out on hybrid GPS-Visual as well as wireless micro-location tracking in order to evaluate their suitability for camera tracking in wide-area or GPS-denied environments. As a result of this investigation a combination of an inertial measurement unit and a camera was chosen as the primary sensory inputs for a hybrid camera tracking system. After following a thorough modelling and mathematical formulation process, a novel and improved hybrid tracking framework was designed, developed and evaluated. The resulting system incorporates an inertial system, a vision-based system and a recursive particle filtering-based stochastic data fusion and state estimation algorithm. The core of the algorithm is a state-space model for motion kinematics which, combined with the principles of multi-view camera geometry and the properties of optical flow and focus of expansion, form the main components of the proposed framework. The proposed solution incorporates a monitoring system, which decides on the best method of tracking at any given time based on the reliability of the fresh vision data provided by the vision-based system, and automatically switches between visual and inertial tracking as and when necessary. The system also includes a novel and effective self-adjusting mechanism, which detects when the newly captured sensory data can be reliably used to correct the past pose estimates. The corrected state is then propagated through to the current time in order to prevent sudden pose estimation errors manifesting as a permanent drift in the tracking output. Following the design stage, the complete system was fully developed and then evaluated using both synthetic and real data. The outcome shows an improved performance compared to existing techniques, such as PTAM and SLAM. The low computational cost of the algorithm enables its application on mobile devices, while the integrated self-monitoring, self-adjusting mechanisms allow for its potential use in wide-area tracking applications.

Engaging in the music set of one’s favorite artist or DJ is oftentimes leading to the result of a powerful and euphoric felt experience, a sensation partly also induced from dancing in beat to the music. In an attempt to simulate a similar dance experience, this user-study examines when a user is let to dance in rhythm to a music playback and in addition, in control of a music playback tempo through the generated dance movements. A proof-of-concept prototype was built and tested in an initial study, followed by a main study where the prototype had been modified and 12 participants participated. A questionnaire was given containing various question statements to be rated through a Likert-scale regarding their subjective experience. Open-ended questions were also included to collect their own opinions. From the results, an enhanced engagement and enjoyment of the music could be identified when being able to manipulate the tempo. / Att engagera sig i ett musik-set av ens favoritartist eller DJ leder ofta till resultatet av en kraftfull och euforisk känsloupplevelse, en känsla delvis framkallat av att man dansar i takt med musiken. I ett försök att simulera en liknande dansupplevelse undersöker denna användarstudie när en användare dansar i rytm till musik och dessutom är i kontroll av tempot genom de skapade dansrörelserna. En proof-of-concept prototyp konstruerades och testades i en första studie, följt av en huvudstudie där prototypen hade modifierats och 12 deltagare deltog. Ett frågeformulär gavs med olika frågor som skulle bedömas via en Likert-skala, med avseende på deras subjektiva erfarenhet. Öppna frågor ingick också för att samla deras egna åsikter. Från resultaten kunde ett ökat engagemang och en förhöjd njutning av musiken identifieras när man kunde manipulera tempot.