| 1. |
- Callmer, Jonas, 1981-
(author)
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Topics in Localization and Mapping
- 2011
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Licentiate thesis (other academic/artistic)abstract
- The need to determine ones position is common and emerges in many different situations. Tracking soldiers or a robot moving in a building or aiding a tourist exploring a new city, all share the questions ”where is the unit?“ and ”where is the unit going?“. This is known as the localization problem.Particularly, the problem of determining ones position in a map while building the map at the same time, commonly known as the simultaneous localization and mapping problem (slam), has been widely studied. It has been performed in cities using different land bound vehicles, in rural environments using au- tonomous aerial vehicles and underwater for coral reef exploration. In this thesis it is studied how radar signals can be used to both position a naval surface ves- sel but also to simultaneously construct a map of the surrounding archipelago. The experimental data used was collected using a high speed naval patrol boat and covers roughly 32 km. A very accurate map was created using nothing but consecutive radar images.A second contribution covers an entirely different problem but it has a solution that is very similar to the first one. Underwater sensors sensitive to magnetic field disturbances can be used to track ships. In this thesis, the sensor positions them- selves are considered unknown and are estimated by tracking a friendly surface vessel with a known magnetic signature. Since each sensor can track the vessel, the sensor positions can be determined by relating them to the vessel trajectory. Simulations show that if the vessel is equipped with a global navigation satellite system, the sensor positions can be determined accurately.There is a desire to localize firefighters while they are searching through a burn- ing building. Knowing where they are would make their work more efficient and significantly safer. In this thesis a positioning system based on foot mounted in- ertial measurement units has been studied. When such a sensor is foot mounted, the available information increases dramatically since the foot stances can be de- tected and incorporated in the position estimate. The focus in this work has therefore been on the problem of stand still detection and a probabilistic frame- work for this has been developed. This system has been extensively investigated to determine its applicability during different movements and boot types. All in all, the stand still detection system works well but problems emerge when a very rigid boot is used or when the subject is crawling. The stand still detection frame- work was then included in a positioning framework that uses the detected stand stills to introduce zero velocity updates. The system was evaluated using local- ization experiments for which there was very accurate ground truth. It showed that the system provides good position estimates but that the estimated heading can be wrong, especially after quick sharp turns.
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| 2. |
- Eidehall, Andreas
(author)
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An Automotive Lane Guidance System
- 2004
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Licentiate thesis (other academic/artistic)abstract
- Automotive lane guidance systems, usually referred to as Lane Keeping Aid or Lane Keeping System, are designed to prevent or warn the driver of lane departure. They typically use a buzzer to alert the driver or a steering wheel torque to actually steer the vehicle back into the center of the lane. Emergency Lane Assist (ELA) combines conventional lane guidance systems with a threat assessment module that tries to activate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure manoeuvres.Such a threat assessment algorithm is dependent on detailed information about the vehicle surroundings, i.e., positions and motion of other vehicles, but also information about road and lane geometry parameters such as lane width and road curvature. The thesis demonstrates that the lane estimate can be improved by using an integrated filter that combines information from object and lane tracking. This is done by introducing a road aligned, curved coordinate system which also brings other advantages when it comes to modelling and prediction.Evaluation of the integrated tracking system has been carried out on real data and the ELA decision algorithm has been tested in a demonstrator. ELA successfully distinguishes between dangerous and safe lane changes ona small set of test scenarios and is, if activated, able to take control of the vehicle and put it in a safe position in the original lane.
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| 3. |
- Elbornsson, Jonas
(author)
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Equalization of Distortion in A/D Converters
- 2001
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Licentiate thesis (other academic/artistic)abstract
- Modern communication systems require A/D converters with very high sample rate and high accuracy. CMOS technology is suitable for integrating A/D converters on a chip at a low cost and low power consumption. However, the CMOS manufacturing process is quite inaccurate, which leads to errors in the A/D converters.Traditionally the A/D converters are calibrated after they are manufactured to correct these errors. This is a time-consuming and costly process. The characteristics of an A/D converter normally change during its lifetime due to, for instance, temperature changes and aging. This cannot be compensated for in the calibration.In this thesis, we investigate how errors in A/D converters can be estimated and corrected without the need for calibration. The estimation should be done using only the signal that is used in the application.Three different types of errors are discussed in this thesis. The first type of error is static nonlinear errors caused by component inaccuracies in CMOS technology. Two methods are proposed for estimation and correction of these errors. The most general method requires only that the amplitude distribution is smooth. With the other method the performance is a little better but it requires knowledge of the amplitude distribution of the input signal. The estimation methods are evaluated on simulated data and data from a real A/D converter.The second type of error is dynamic nonlinear errors in the sample-and hold circuit which inevitably occurs when the sample rate increases. Some ideas about how to correct these errors are discussed.The third type of error is timing errors in time interleaved A/D converters, where the idea is to increase sample rate by parallelization of the conversion. A method for estimation and correction of these errors is proposed. This method requires that most of the signal energy is limited to a frequency band below about 1=3 of the Nyquist frequency, but requires no other knowledge of the signal. This estimation method is evaluated on simulated data.
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| 4. |
- Evestedt, Niclas
(author)
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Sampling Based Motion Planning for Heavy Duty Autonomous Vehicles
- 2016
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Licentiate thesis (other academic/artistic)abstract
- The automotive industry is undergoing a revolution where the more traditional mechanical values are replaced by an ever increasing number of Advanced Driver Assistance Systems (ADAS) where advanced algorithms and software development are taking a bigger role. Increased safety, reduced emissions and the possibility of completely new business models are driving the development and most automotive companies have started projects that aim towards fully autonomous vehicles. For industrial applications that provide a closed environment, such as mining facilities, harbors, agriculture and airports, full implementation of the technology is already available with increased productivity, reliability and reduced wear on equipment as a result. However, it also gives the opportunity to create a safer working environment when human drivers can be removed from dangerous working conditions. Regardless of the application an important part of any mobile autonomous system is the motion planning layer. In this thesis sampling-based motion planning algorithms are used to solve several non-holonomic and kinodynamic planning problems for car-like robotic vehicles in different application areas that all present different challenges.First we present an extension to the probabilistic sampling-based Closed-Loop Rapidly exploring Random Tree (CL-RRT) framework that significantly increases the probability of drawing a valid sample for platforms with second order differential constraints. When a tree extension is found infeasible a new acceleration profile that tries to brings the vehicle to a full stop before the collision occurs is calculated. A resimulation of the tree extension with the new acceleration profile is then performed. The framework is tested on a heavy-duty Scania G480 mining truck in a simple constructed scenario.Furthermore, we present two different driver assistance systems for the complicated task of reversing with a truck with a dolly-steered trailer. The first is a manual system where the user can easily construct a kinematically feasible path through a graphical user interface. The second is a fully automatic planner, based on the CL-RRT algorithm where only a start and goal position need to be provided. For both approaches, the internal angles of the trailer configuration are stabilized using a Linear Quadratic (LQ) controller and path following is achieved through a pure-pursuit control law. The systems are demonstrated on a small-scale test vehicle with good results.Finally, we look at the planning problem for an autonomous vehicle in an urban setting with dense traffic for two different time-critical maneuvers, namely, intersection merging and highway merging. In these situations, a social interplay between drivers is often necessary in order to perform a safe merge. To model this interaction a prediction engine is developed and used to predict the future evolution of the complete traffic scene given our own intended trajectory. Real-time capabilities are demonstrated through a series of simulations with varying traffic densities. It is shown, in simulation, that the proposed method is capable of safe merging in much denser traffic compared to a base-line method where a constant velocity model is used for predictions.
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| 5. |
- Geijer Lundin, Erik
(author)
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Uplink Load in CDMA Cellular Systems
- 2003
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Licentiate thesis (other academic/artistic)abstract
- Cellular mobile systems designed to handle multimedia services are currently being developed. The primary goal for any mobile system is to provide a satisfactory quality of service, both to operators and customers. Providing good quality of service while maintaining system stability requires accurate knowledge of the system load. In particular, it is important to be able to predict how a resource management decision will affect the stability of the network. This thesis addresses the problem of characterizing and estimating the uplink load in a cellular system using CDMA (Code Division Multiple Access) in the radio interface.Uplink load can be related directly to the uplink power control problem of finding transmitter powers to support the users' quality of service requirements. This yields a rather theoretical view. Another way of looking at uplink load is to relate it to the total received power users induce in the base station antennas. Both of these views are handled and relations between them are established in this thesis.The literature survey on uplink load provided in this work concludes that practical estimates of the uplink load are generally what can be referred to as decentralized estimates; they use information gathered only in the immediate vicinity of the estimates' host node. As an alternative to these estimates, a number of centralized estimates based on information readilyavailable to the system are proposed. The usage of information from several cells makes them more sensitive to the soft capacity inherent in all CDMA cellular systems.Extensive simulations in an advanced WCDMA (Wideband Code Division Multiple Access) simulator show that the estimates statistically perform well and the performance is insensitive to non uniform traffic load.In the time domain, the load approximation can be described as oscillations superimposed on a slowly varying bias. If occasional high loads can be accepted, a non-oscillative signal representing the uplink load can be used to further increase the utilization of the resources. An algorithm is proposed to estimate the bias and a prediction of it.
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| 6. |
- Gillberg, Jonas, 1975-
(author)
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Methods for Frequency Domain Estimation of Continuous-Time Models
- 2004
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Licentiate thesis (other academic/artistic)abstract
- Approaching parameter estimation from the discrete-time domain is the dominating paradigm in system identification. Identification of continuous-time models on the other hand is motivated by the fact that modelling of physical systems often take place in continuous-time. For many practical applications there is also a genuine interest in the parameters connected to these physical models. In the black-box discrete-time modelling framework however, the identified parameters often lack a physical interpretation.Uniform sampling has also been a standard assumption. A single sensor delivering measurements at a constant rate has been considered as the ideal situation. With the advent of networked asynchronous sensors the validity of this assumption has however changed. In fields such as economics and finance, uniform sampling might not be practically possible. This indicates a need for methods coping with non-uniform sampling.In the first part of this thesis the problem of estimation of irregularly sampled continuous-time ARMA models in the frequency domain is treated. In this process, the mode! output is assumed to be piecewise constant or piecewise linear, and an approximation of the continuous-time spectral density is calculated. Maximum Likelihood estimation in the frequency domain is then used to obtain parameter estimates. Rules of thumb concerning the mode! bias and variance are derived and used in order to select the frequencies to be used in estimation. Finally, the methods are applied to a tire pressure estimation problem.The second part ofthe thesis treats frequency domain identification of continuoustime ARMA and OE models for uniformly sampled data. Here the end objective is to inspire improved interpolation schemes which excel over the piecewise-linear and piecewise-constant approximations used in the first part. The result is a method which estimates the continuous-time spectrum/Fourier transform from its discretetime counterpart.
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| 7. |
- Kok, Manon
(author)
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Probabilistic modeling for positioning applications using inertial sensors
- 2014
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Licentiate thesis (other academic/artistic)abstract
- In this thesis, we consider the problem of estimating position and orientation (6D pose) using inertial sensors (accelerometers and gyroscopes). Inertial sensors provide information about the change in position and orientation at high sampling rates. However, they suffer from integration drift and hence need to be supplemented with additional sensors. To combine information from the inertial sensors with information from other sensors we use probabilistic models, both for sensor fusion and for sensor calibration.Inertial sensors can be supplemented with magnetometers, which are typically used to provide heading information. This relies on the assumption that the measured magnetic field is equal to a constant local magnetic field and that the magnetometer is properly calibrated. However, the presence of metallic objects in the vicinity of the sensor will make the first assumption invalid. If the metallic object is rigidly attached to the sensor, the magnetometer can be calibrated for the presence of this magnetic disturbance. Afterwards, the measurements can be used for heading estimation as if the disturbance was not present. We present a practical magnetometer calibration algorithm that is experimentally shown to lead to improved heading estimates. An alternative approach is to exploit the presence of magnetic disturbances in indoor environments by using them as a source of position information. We show that in the vicinity of a magnetic coil it is possible to obtain accurate position estimates using inertial sensors, magnetometers and knowledge of the magnetic field induced by the coil.We also consider the problem of estimating a human body’s 6D pose. For this, multiple inertial sensors are placed on the body. Information from the inertial sensors is combined using a biomechanical model which represents the human body as consisting of connected body segments. We solve this problem using an optimization-based approach and show that accurate 6D pose estimates are obtained. These estimates accurately represent the relative position and orientation of the human body, i.e. the shape of the body is accurately represented but the absolute position can not be determined.To estimate absolute position of the body, we consider the problem of indoor positioning using time of arrival measurements from an ultra-wideband (uwb) system in combination with inertial measurements. Our algorithm uses a tightlycoupled sensor fusion approach and is shown to lead to accurate position and orientation estimates. To be able to obtain position information from the uwb measurements, it is imperative that accurate estimates of the receivers’ positions and clock offsets are known. Hence, we also present an easy-to-use algorithm to calibrate the uwb system. It is based on a maximum likelihood formulation and represents the uwb measurements assuming a heavy-tailed asymmetric noise distribution to account for measurement outliers.
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| 8. |
- Mathai, George
(author)
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Direction of Arrival Estimation of Wideband Acoustic Wavefields in a Passive Sensing Environment
- 2015
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Licentiate thesis (other academic/artistic)abstract
- Direction Of Arrival (DOA) estimation has been an active research area for many decades because of its usefulness in many fields, such as wireless communication, navigation, astronomy, surveillance, medicine etc. In DOA estimation, emitted wavefields from unknown sources are measured with the aid of an array of sensors, and this information is then processed to determine various parameters of the sources including the angle between each source and the array. The emitted wavefields could be electromagnetic, seismic or acoustic.Many of the existing methods for DOA estimation were developed in the communication area for dealing with electromagnetic radiation. In this work, we are investigating the problem of DOA estimation for wideband acoustic sources using a microphone array. Since microphones are getting popular in wireless ground sensor networks, this research direction could potentially offer a cost efficient and passive way for detecting, tracking and classifying moving targets. In this thesis, several existing spectral based wideband DOA methods suitable for this purpose are surveyed. Further, a new method based on local polynomial expansion (LPE) is proposed. The performance of these methods is compared by testing them on both simulated and real data, where the real data come from practical field tests with different motorized vehicles. The LPE method is found to be quite competitive for this kind of wideband acoustic sources in real environments.
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| 9. |
- Nordlund, Per-Johan
(author)
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Sequential Monte Carlo Filters and Integrated Navigation
- 2002
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Licentiate thesis (other academic/artistic)abstract
- In this thesis we consider recursive Bayesian estimation in general, and sequential Monte Carlo filters in particular, applied to integrated navigation. Based on a large number of simulations of the model, the sequential Monte Carlo filter, also referred to as particle filter, provides an empirical estimate of the full posterior probability density of the system. The particle filter provide a solution to the general nonlinear, non-Gaussian filtering problem. The more nonlinear system, or the more non-Gaussian noise, the more potential particle filters have.Although very promising even for high-dimensional systems, sequential Monte Carlo methods suer from being more or less computer intensive. However, many systems can be divided into two parts, where the first part is nonlinear and the second is (almost) linear conditionally upon the first. By applying the particle filter only on the severly nonlinear part of lower dimension, the computational load can be significantly reduced. For the remaining conditionally (almost) linear partwe apply (linearized) linear filters, such as the (extended) Kalman filter. From a Bayesian point of view, the result from the different filters can be seen as marginal posterior probability densities. The full posterior density is then computed by combining the results from the separate filters using Bayes' rule. The technique of marginalising the complete posterior density and solve the linear parts analytically is referred to as Rao-Blackwellization.The application considered here is integrated aircraft navigation. Integrated navigation refers to the combination of outputs from two or more navigation sensors to yield a more accurate and reliable overall solution. The sensors we are dealing with are inertial navigation and terrain-aided positioning, meaning that we combine two systems which are high-dimensional and highly nonlinear respectively. The integrated navigation application is a typical system which consists of both linearand nonlinear elements. We show that by applying the efficent particle filter based on Rao-Blackwellization we obtain nearly optimal accuracy for a tractable amount of computational load.
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| 10. |
- Persson, Niclas
(author)
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Event Based Sampling with Application to Spectral Estimation
- 2002
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Licentiate thesis (other academic/artistic)abstract
- In this thesis event based sampling, estimation of a single resonance frequency and the application indirect tire pressure monitoring system are studied.Event based sampling is an alternative to traditional uniform or equidistant sampling. In event based sampled systems, signals are sampled only when certain pre-defined events take place. Event based sampling occurs naturally in many contexts such as motion systems where angles and positions are measured. In this thesis special attention is paid to rotating axles where the position is measured with a rotational speed sensor. Due to production tolerances such a sensor has a nonideal performance. This causes a periodic error in the event based sampled signal which in many cases cannot be neglected. Two different methods for elimitating the sensor errors are proposed.To be able to use standard tools for analyzing the signal from the rotational speed sensor, the signal is interpolated to a uniformly sampled signal. A desirable feature of the interpolation is to incorporate a lowpass filter to avoid aliasing. We investigate and compare three different methods, all based on a non-parametric regression.A survey of different methods to estimate a single resonance frequency in the rotational speed signal is presented including aspects of estimation accuracy and computational complexity.As an application of event based sampling and spectral estimation, a Tire Pressure Monitoring System (TPMS) is designed and analyzed. The TPMS is based on event based sampled measurements from a wheel speed sensor. The tire is modeled as a spring-damper system. The idea is to monitor the resonance frequency caused by the spring-damper system. This frequency is correlated with the inflation pressure, and by monitoring the resonance frequency, it is possible to detect inflation pressure changes. The system is implemented and tested in a real vehicle with promising results.
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