Hydrauliska stötdämpare har länge varit en central komponent på både bilar och motorcyklar. Stötdämpare påverkar fordonets komfort, väghållning och köregenskaper. Dessa olika egenskaper kräver ofta helt olika typer av dämpning och med vanliga passiva dämpare blir resultatet ofta en kompromiss av samtliga dessa. Kompromisserna har lett till utvecklingen av en stötdämpare med ställbar dämparkarakteristik som är tänkt att ersätta passiva dämpare. Öhlins Racing säljer idag ett semiaktivt stötdämparsystem som kallas CES, Continously controlled Electronic Suspension, där dämparkarakteristiken styrs av en tryck- och flödeskompenserad CES-ventil. CES-ventilen är strömstyrd via en ECU, Electronic Control Unit, som monteras på fordonet. Möjligheterna att förbättra fordonens egenskaper är stora men regleringen av dämparen är kritisk för prestandan. Examesarbetet syftar till att via experimentella laborationstester förbättra dämparens prestanda genom att förbättra styrningen av systemet. Det visar sig att den nuvarande reglersystemet lider av en tidsfördröjning, varför en stor del av examensarbetet fokuserar på att minimera detta. Resultaten visar att då hastigheten skattas med ett Kalmanfilter, som tar hänsyn till både dämparens position och acceleration, kan tidsfördröjningar nästan helt elimineras. Elimineringen av tidsfördröjning visar sig förbättra prestandan avsevärt. För att ytterligare öka prestandan hos systemet introduceras även en accelerationsframkoppling.

<p>Detta examensarbete är en del av SNOD-projektet vid Totalförsvarets Forskningsinstitut (FOI), vars syfte är att utveckla ett sensorsystem med infraröda- och videosensorer och integrerat navigationssystem. Sensorsystemet är placerat i en kameragimbal och kan användas på rörliga plattformar, t ex UAV:er, för övervakning och rekognoscering. Gimbalen är till för att möjliggöra inriktning av sensorerna i önskad riktning.</p><p>Detta examensarbete behandlar en metod för inmätning av målkoordinater från den rörliga plattformen, det s k QWIP/MASP-systemet. Detta efterliknar ett UAV-system. Metoden för inmätning baseras på ett extended information filter där målkoordinaterna filtreras fram. Mätningarna bygger på data från en bildbaserad målföljare med på IR- och videodata.</p><p>För att förbättra inmätningen har en metod för planering av plattformens rörelsebana tagits fram. Denna metod bygger en referensbana för plattformen som maximerar informationen i informationsfiltret.</p><p>Metoderna har utvecklats för implementering i den aktuella sensorplattformen, QWIP/MASP-systemet. För att övervaka och styra denna plattform har ett grafiskt användargränssnitt tagits fram för operatörsstöd.</p> / <p>This thesis is a part of the SNOD project at Swedish Defence Research Agency (FOI), which aims at developing a sensor system consisting of infrared and video sensors and an integrated navigation system. The sensor system is placed in a camera gimbal and will be used on moving platforms, e.g. UAVs, for surveillance and reconnaissance. The gimbal is a device that makes it possible for sensors to be pointed in a desired direction.</p><p>In this thesis a method for estimating target position using a moving platform is discussed. This method is based on the extended information filter, where bearingonly measurements are given by infrared and video images processed through a target tracker. Tests and evaluations are done with data from the QWIP/MASP-system, which is an UAV surrogate developed at FOI.</p><p>To improve target position estimation, a path planning method using information theory has been developed. This method is based on maximizing the expected information of the information filter.</p><p>These methods have been developed for implementation in the QWIP/MASP-system. A user interface for this system has also been developed to support the operator.</p>

Detta examensarbete är en del av SNOD-projektet vid Totalförsvarets Forskningsinstitut (FOI), vars syfte är att utveckla ett sensorsystem med infraröda- och videosensorer och integrerat navigationssystem. Sensorsystemet är placerat i en kameragimbal och kan användas på rörliga plattformar, t ex UAV:er, för övervakning och rekognoscering. Gimbalen är till för att möjliggöra inriktning av sensorerna i önskad riktning. Detta examensarbete behandlar en metod för inmätning av målkoordinater från den rörliga plattformen, det s k QWIP/MASP-systemet. Detta efterliknar ett UAV-system. Metoden för inmätning baseras på ett extended information filter där målkoordinaterna filtreras fram. Mätningarna bygger på data från en bildbaserad målföljare med på IR- och videodata. För att förbättra inmätningen har en metod för planering av plattformens rörelsebana tagits fram. Denna metod bygger en referensbana för plattformen som maximerar informationen i informationsfiltret. Metoderna har utvecklats för implementering i den aktuella sensorplattformen, QWIP/MASP-systemet. För att övervaka och styra denna plattform har ett grafiskt användargränssnitt tagits fram för operatörsstöd. / This thesis is a part of the SNOD project at Swedish Defence Research Agency (FOI), which aims at developing a sensor system consisting of infrared and video sensors and an integrated navigation system. The sensor system is placed in a camera gimbal and will be used on moving platforms, e.g. UAVs, for surveillance and reconnaissance. The gimbal is a device that makes it possible for sensors to be pointed in a desired direction. In this thesis a method for estimating target position using a moving platform is discussed. This method is based on the extended information filter, where bearingonly measurements are given by infrared and video images processed through a target tracker. Tests and evaluations are done with data from the QWIP/MASP-system, which is an UAV surrogate developed at FOI. To improve target position estimation, a path planning method using information theory has been developed. This method is based on maximizing the expected information of the information filter. These methods have been developed for implementation in the QWIP/MASP-system. A user interface for this system has also been developed to support the operator.

<p>This master thesis includes a description of how a number of sensors are put together in a sensor platform. It also gives a description of how localization and mapping has been performed with data collected from the sensor platform. </p><p>Localization is a prerequisite for most of the tasks that can be requested from an autonomous mobile robot. In many situations the GPS signal is not available and hence an additional localization system is required. One approach is to apply localization based on landmarks extracted from the robots surrounding. Using e.g. a scanning range finding laser landmarks can be extracted from the robots surrounding. </p><p>Localization and mapping is performed with an extended kalman filter where the robots and the landmarks positions are represented as states. The positioning algorithm is finally tested in indoor environment using lines and line segments as landmarks. The landmarks are extracted from measurement data from the scanning range finding laser. This master thesis is a part of a larger project which purpose is to investigate the benefit of cooperation between several mobile robots.</p>

This master thesis includes a description of how a number of sensors are put together in a sensor platform. It also gives a description of how localization and mapping has been performed with data collected from the sensor platform. Localization is a prerequisite for most of the tasks that can be requested from an autonomous mobile robot. In many situations the GPS signal is not available and hence an additional localization system is required. One approach is to apply localization based on landmarks extracted from the robots surrounding. Using e.g. a scanning range finding laser landmarks can be extracted from the robots surrounding. Localization and mapping is performed with an extended kalman filter where the robots and the landmarks positions are represented as states. The positioning algorithm is finally tested in indoor environment using lines and line segments as landmarks. The landmarks are extracted from measurement data from the scanning range finding laser. This master thesis is a part of a larger project which purpose is to investigate the benefit of cooperation between several mobile robots.

This Masters Thesis considers tracking of ground targets. Since ground targets often are difficult to detect with sensors a track is easily lost in ground target tracking. The main question in this thesis is whether information on close targets and observations of them can be used to make the tracking more reliable. An algorithm using Kalman filters and JPDA-association to create a group track for vehicles travelling together has been implemented in Matlab. Using the state of the centre of the group the state of a vehicle in the group can be updated. The result of updating vehicles states with the state of the centre of the group is that the relative decrease in lost tracks is improved with up to 53 % in the studied case.

<p>This Masters Thesis considers tracking of ground targets. Since ground targets often are difficult to detect with sensors a track is easily lost in ground target tracking. The main question in this thesis is whether information on close targets and observations of them can be used to make the tracking more reliable. An algorithm using Kalman filters and JPDA-association to create a group track for vehicles travelling together has been implemented in Matlab. Using the state of the centre of the group the state of a vehicle in the group can be updated. The result of updating vehicles states with the state of the centre of the group is that the relative decrease in lost tracks is improved with up to 53 % in the studied case.</p>

This thesis is divided in to two different parts. The first part includes examination of the measurementsystem of an industrial robot using a resolver sensor. The main focus is on methods for suppressing noise in the angularvelocity signal without increasing timedelay. Five different methods are investigated. Three of these are based on oversampling: burstsamplingmethod, meanvaluemethod and correlationmethod. The meanvaluemethod and the correlationmethod have given good results. The two other methods are: extended kalmanfiltering and computation of the angular velocity without using numeric method to compute the angle. Extended kalmanfilter gives the overall best result. In part two the control structure design of an industrial robot has been studied and how different sampling times and motorinertias affect the disturbance rejection and stability of the control loop. Different control structure designs have also been studied with the aim to suppress disturbances. Mainly H-infinity and GIMC designs have been compared with an ordinary PID controller. Here it can be shown that both the H-infinity and the GIMC controller yields good disturbance rejection. But both the methods lack in the robustness of model uncertainty.

Many traffic incidents are due to the driver’s lack of attention, resulting in dangerous lane departures, either sliding off theroad or into the oppose lane. These kinds of incidents often have serious outcomes, which has led to much effort being concentrated on preventing or lessening the damages when the incident is already a fact, for example by installing safety belts and air bags. These measures may be considered to be acts of so-called passive safety. Active safety on the other hand, means that the safety systems intervene before the incidents have occurred. Lane Keeping Aid (LKA), which has been developed and implemented in this master thesis project, is a system designed to support the driver in the lateral axis in situations when unwanted lane departure is an evident risk. To be able to determine when the system should intervene and support the driver, information regarding how the driver handles the vehicle, along with the vehicle’s position and direction in the lane, is essential. The car’s position may be obtained by installing a camera in the vehicle. The information needed regarding other things, e.g. the car’s position in relation to the lane, is obtained by using a Kalmanfilter, which is based on a physically developed model, and which estimates the mentioned distances. Based on measurements and estimated values, it is possible for the LKA system to calculate an assistance torque, aimed at decreasing the lateral deviation from the centre of the lane. An electric power steering, instead of a conventional hydraulic steering servo is then used to produce the torque. The LKA system has been developed in a simulation environment using Simulink before being implemented, in order to monitor the function of the system before beginning actual testdrives. Furthermore, real measurement data given at driving with the test vehicle has been used to adjust and test the function. The results from the project’s first phase, in the simulation environment, show that the estimated values from the Kalmanfilter correlates well with real test data. Simulations with real measurement data show that the system functions as intended. Finally, it may also be mentioned, that the system has yet not been fully tested in a vehicle equipped with an electric power steering, which ought to be included in future development of the system.

<p>This thesis is divided in to two different parts. The first part includes examination of the measurementsystem of an industrial robot using a resolver sensor. The main focus is on methods for suppressing noise in the angularvelocity signal without increasing timedelay. Five different methods are investigated. Three of these are based on oversampling: burstsamplingmethod, meanvaluemethod and correlationmethod. The meanvaluemethod and the correlationmethod have given good results. The two other methods are: extended kalmanfiltering and computation of the angular velocity without using numeric method to compute the angle. Extended kalmanfilter gives the overall best result. </p><p>In part two the control structure design of an industrial robot has been studied and how different sampling times and motorinertias affect the disturbance rejection and stability of the control loop. Different control structure designs have also been studied with the aim to suppress disturbances. Mainly H-infinity and GIMC designs have been compared with an ordinary PID controller. Here it can be shown that both the H-infinity and the GIMC controller yields good disturbance rejection. But both the methods lack in the robustness of model uncertainty.</p>