| 1. |
- Axelsson, Patrik, 1985-
(författare)
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On Sensor Fusion Applied to Industrial Manipulators
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the main tasks for an industrial robot is to move the end-effector in a predefined path with a specified velocity and acceleration. Different applications have different requirements of the performance. For some applications it is essential that the tracking error is extremely low, whereas other applications require a time optimal tracking. Independent of the application, the controller is a crucial part of the robot system. The most common controller configuration uses only measurements of the motor angular positions and velocities, instead of the position and velocity of the end-effector.The development of new cost optimised robots have introduced unwanted flexibilities in the joints and the links. It is no longer possible to get the desired performance and robustness by only measuring the motor angular positions. This thesis investigates if it is possible to estimate the end-effector position when an accelerometer is mounted at the end-effector. The main focus is to investigate Bayesian estimation methods for state estimation, here represented by the extended Kalman filter (EKF) and the particle filter (PF).A simulation study is performed on a two degrees of freedom industrial robot model using an EKF. The study emphasises three important problems to take care of in order to get a good performance. The first one is related to model errors which in general requires better identification methods. The second problem is about tuning of the EKF, i.e., the choice of covariance matrices for the measurement and process noise. It is desirable to have an automatic tuning procedure which minimises the estimation error and is robust to initial conditions of the tuned parameters. A variant of the expectation maximisation (EM) algorithm is proposed for estimation of the process noise covariance matrix Q. The EM algorithm iteratively estimates the unobserved state sequence and the matrix Q based on the observations of the process, where the extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence.The third problem considers the orientation and position of the accelerometer mounted to the end-effector. A novel method to find the orientation and position of the triaxial accelerometer is proposed and evaluated on experimental data. The method consists of two consecutive steps, where the first is to estimate the orientation of the sensor from static experiments. In the second step the sensor position relative to the robot base is identified using sensor readings when the sensor moves in a circular path and where the sensor orientation is kept constant in a path fixed coordinate system.Finally, experimental evaluations are performed on an ABB IRB4600 robot. Different observers using the EKF, EKS and PF with different estimation models are proposed. The estimated paths are compared to the true path measured by a laser tracking system. There is no significant difference in performance between the six observers. Instead, execution time, model complexities and implementation issues have to be considered when choosing the method.
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| 2. |
- Blom, Jonas
(författare)
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Power Control in Cellular Radio Systems
- 1998
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The primary goal of cellular radio systems, is to provide communication services to a large number of mobile users. Due to the rapid expansion of the market in this area, the available resources have to be used efficiently. The main issue in this thesis is methods to assign appropriate transmission powers, given coarsely quantized measurements, in order to meet the quality requirements from the users despite various disturbances.We propose a concept of a power regulator comprising the steps of estimating relevant quantities, handling quality specications, and controlling the powers. With this setting, the power controlling component relates directly to the mainstream of the algorithms proposed to date.For practical reasons, it is necessary to control the powers in a distributed fashion, and these distributed algorithms can be seen as local control loops. The effects of time delays and power output constraints in these loops are analyzed with respect to stability, using root locus techniques and describing functions. We emphasize the importance of identifying these time delays and constraints in order to choose the appropriate controller parameters for stable operation. The relevance of the local stability results on the overall system level is discussed, and further analyzed in a simulation environment, which has been developed.The literature is surveyed, and the contributions are classified with respect to a common framework in order to stress their similarities and differences. We show that an integrating controller forms the basis for the most popular algorithms. Methods for convergence analysis are investigated and related to the theory of linear systems. These methods are applied when proving global convergence of the integrating controller.The power control strategies are evaluated under more realistic circumstances in an environment simulating the operation of a GSM system. Comparing the results when using different power control algorithms we note that the proposed concept performs better than the algorithms proposed to date, both in terms of transmission quality of service and capacity.
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| 3. |
- Callmer, Jonas, 1981-
(författare)
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Topics in Localization and Mapping
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 4. |
- Eidehall, Andreas
(författare)
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An Automotive Lane Guidance System
- 2004
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 5. |
- Elbornsson, Jonas
(författare)
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Equalization of Distortion in A/D Converters
- 2001
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 6. |
- Evestedt, Niclas
(författare)
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Sampling Based Motion Planning for Heavy Duty Autonomous Vehicles
- 2016
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 7. |
- Geijer Lundin, Erik
(författare)
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Uplink Load in CDMA Cellular Systems
- 2003
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 8. |
- Gillberg, Jonas, 1975-
(författare)
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Methods for Frequency Domain Estimation of Continuous-Time Models
- 2004
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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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| 9. |
- Gustafsson, Fredrik
(författare)
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Optimal Segmentation of Linear Regression Parameters
- 1990
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The problem of detecting multiple changes in the dynamical properties of a measured signal, which we call segmentation, is studied. A Bayesian model-based approach is used. The signal is supposed to be described by a linear regression. The posterior distribution for the change instants is first derived for a quite general signal model. Three special choices of signal model are then proposed for segmentation. The maximum a posteriori (MAP) estimate is studied. It is shown that it contains the estimates from the maximum likelihood method and the generalized likelihood ratio test as special cases.This posterior distribution contains a number of components which increases exponentially in the number of measurements, t. Nevertheless, it is shown that under certain assumptions on the parameter variation structure, the number of components that really ha veto be examined increases considerably less than t. This exact pruning possibility is shown to be asymptotically efficient in the ratio between the jump magnitude and the noise variance.For the general signal model a recursive search scheme is proposed to approximate the MAP estimate. Segmentation examples and other possible applications of the search scheme are given.
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| 10. |
- Hendeby, Gustaf, 1978-
(författare)
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Fundamental Estimation and Detection Limits in Linear Non-Gaussian Systems
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Many methods used for estimation and detection consider only the mean and variance of the involved noise instead of the full noise descriptions. One reason for this is that the mathematics is often considerably simplified this way. However, the implications of the simplifications are seldom studied, and this thesis shows that if no approximations are made performance is gained. Furthermore, the gain is quantified in terms of the useful information in the noise distributions involved. The useful information is given by the intrinsic accuracy, and a method to compute the intrinsic accuracy for a given distribution, using Monte Carlo methods, is outlined.A lower bound for the covariance of the estimation error for any unbiased estimator s given by the Cramér-Rao lower bound (CRLB). At the same time, the Kalman filter is the best linear unbiased estimator (BLUE) for linear systems. It is in this thesis shown that the CRLB and the BLUE performance are given by the same expression, which is parameterized in the intrinsic accuracy of the noise. How the performance depends on the noise is then used to indicate when nonlinear filters, e.g., a particle filter, should be used instead of a Kalman filter. The CRLB results are shown, in simulations, to be a useful indication of when to use more powerful estimation methods. The simulations also show that other techniques should be used as a complement to the CRLB analysis to get conclusive performance results.For fault detection, the statistics of the asymptotic generalized likelihood ratio (GLR) test provides an upper bound on the obtainable detection performance. The performance is in this thesis shown to depend on the intrinsic accuracy of the involved noise. The asymptotic GLR performance can then be calculated for a test using the actual noise and for a test using the approximative Gaussian noise. Based on the difference in performance, it is possible to draw conclusions about the quality of the Gaussian approximation. Simulations show that when the difference in performance is large, an exact noise representation improves the detection. Simulations also show that it is difficult to predict the exact influence on the detection performance caused by substituting the system noise with Gaussian noise approximations.
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