Micro Aerial Vehicles and especially multi rotors are gaining more and more attention for accomplishing complex tasks, considering their simple mechanical design and their versatile movement. MAVs are ideal candidates to perform tasks autonomously, to work safely in close proximity and in collaboration with humans, and to operate safely and effectively in natural human environments, like infrastructure inspection-maintenance, underground mine operations and surveillance missions. Adopting this vision, this thesis contributes in the aerial platform ecosystem that can be summarized by the term Aerial Robotic Worker (ARW). An ARW is characterized, among others, by its advanced capabilities on environmental perception and 3D reconstruction and active aerial manipulation.Using cameras for localization, mapping of an ARW as well as guidance on aerial manipulation is appealing mainly because of the small size and cost of such sensors. Nevertheless, visualinformation provided from the cameras is enormous, posing significant challenges in real-time data processing, while meeting the constraints of these platforms. Additionally, another challenge on visual perception considers the usage of multiple agents that collaboratively perceive their surroundings forming an aerial sensor. This thesis also investigates the applicability of visual SLAM algorithms in uncontrolled and cluttered environments. Furthermore, work will be presented on visual guidance for an aerial manipulator, which is challenging regarding the object detection, tracking and the platform approaching strategies. The first contribution will be the establishment of a flexible virtual stereo rig consisted of MPC controlled MAVs. The advantage of this approach is the varying baseline sensor that is composed from independently moving cameras, adjusting the depth perception accordingly. This method is able to provide the 3D reconstruction of the environment in a sparse pointcloud. The second contribution of this this thesis will examine the single agents in two different scenarios. Initially, experimental trials of commonly used visual sensors in hard and challenging environments will be presented in real scale underground ore mine to evaluate the localization and mapping performance of such technology for potential usage in UAVs. Secondly, theoretical work will be performed regarding attitude regulation of a hexacopter for stable hovering based on visual localization. In this work the time delays induced from the processing should be compensated with a switching control scheme which is able to maintain the stability of the platform. Finally, a third contribution of this thesis will be vision for aerial manipulation. The developed system includes a stereo camera that is attached on the end-effector of the aerial manipulator and is used to provide robust target detection and tracking. The visual feedback is processed to co-localize the aerial agent with the target and generate a waypoint that allows to approach the target.

The two topics at the heart of this thesis are how to improve control of industrial manipulators and how to reason about the role of models in automatic control. On industrial manipulators, two case studies are presented. The first investigates estimation with inertial sensors, and the second compares control by feedback linearization to control based on gain-scheduling. The contributions on the second topic illustrate the close connection between control and estimation in different ways. A conceptual model of control is introduced, which can be used to emphasize the role of models as well as the human aspect of control engineering. Some observations are made regarding block-diagram reformulations that illustrate the relation between models, control and inversion. Finally, a suggestion for how the internal model principle, internal model control, disturbance observers and Youla-Kucera parametrization can be introduced in a unified way is presented.

Robotic systems are nowadays the key technology in a wide variety of applications. The increasing demand for performance of robotic systems is often met by employing a team of cooperating robots for a specific task.When the task carried out by the robots involves manipulation of an object, the multi-robot system is said to perform a cooperative manipulation task.Cooperative manipulation is an important capability for extending the domain of robotic applications.This thesis studies the time-optimal path tracking problem for a cooperative manipulation scenario where an object is rigidly grasped by multiple manipulators. The goal is to move the object along a predefined geometric path in minimum time while satisfying the imposed constraints on the motion. First, it is shown that the time-optimal path tracking problem for cooperative manipulators can be cast as a convex optimization problem. A fundamental property of convex optimization problems is that any locally optimal solution is also a globally optimal one. Furthermore, by recognizing and formulating a problem as a convex optimization problem, it can be solved very reliably and efficiently using interior-point or other methods for convex optimization.These results are presented in two separate studies. In the first one which is a preliminary study, the manipulation setup is a particular setup comprised of two planar manipulators and a bar. Furthermore, the load distribution among the manipulators is considered to be equal. The second study extends the results in the preliminary study to a general scenario with $N$ generic manipulators and an object with a desired orientation during the motion. Here, the load distribution among the manipulators is determined via a generic pseudo-inverse of the grasp matrix that can be chosen by the user.The freedom in the choice of the pseudo-inverse allows to consider different load distributions which can be exploited to account for the potential differences in the capabilities of the manipulators.The second part of this thesis is devoted to finding load distributions that are free of internal forces. A drawback of using multiple manipulators in a cooperative manipulation task is that internal forces can be introduced.Internal forces are forces exerted by the end-effectors at the grasping points that do not contribute to the motion of the manipulated object. While a certain amount of such forces can be useful in some cases, in general they must be avoided to prevent object damage and unnecessary effort of the manipulators.This thesis proposes a new approach to obtain internal force-free load distributions.The proposed approach results in a new pseudo-inverse of the grasp matrix parameterized by coefficients that have the meaning of the inertial parameters of some parts of the object. The freedom in the choice of the parameters of the pseudo-inverse allows to assign different loads to the manipulators. This can be exploited to account for the differences in the power capabilities of the manipulators.The results are further explored for scenarios where the object is three-dimensional and convex and has uniform mass density. Finally, the proposed pseudo-inverse is combined with the results in the first part of the thesis to solve the problem of time-optimal cooperative path tracking subject to zero internal forces during the motion.

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.

The current year, 2021, started with the landing of the Perseverance mission and the flight of the first drone on Mars, marking an important event in the history of space exploration. The exploration of new environments would be easier and characterised by the absence of various obstacles if implementing a larger use of drones. This thesis project represents a first attempt to design a space UAV based on thrusters, in order to permit its use also in vacuum: the purpose is to demon- strate the possibility to use and control this new space technology after selecting the adequate components. Lists of environments and thrusters are mentioned to give a general idea of the possibilities; afterwards, a trade-off between all these choices is done, picking HPGP thrusters and Interamnia 704 as exploration site. The design included offers a great glimpse about all the necessary subsystems and focuses on propulsion and GNC subsystem. The second part of the document aims the attention on the dynamics of the pro- posed platform, developing a mathematical model and the state space form. These information are used for the guidance and control algorithms: Explicit Guidance and Non-Linear Dynamic Inversion control. The results found are then shown and verified: demonstrating the feasibility of the drone and its autonomous control for exploration and mapping purposes.

In this thesis speed estimation of wheeled indoor vehicles based on vibrationsin the wheels is studied. Suitable applications include localization on wheeledindoor equipment, where wheel speed sensors are impractical or cannot be installed.Utilizing the inertial measurement unit installed on a tag, the accelerometerscan provide information about the fundamental frequency and harmonicsof the wheel. The information is provided through the vibration components,embedded in the accelerometer signal, and the speed of the vehicle is proportionalto the fundamental frequency. To enable inertial navigation of the vehiclea Kalman filter is used, allowing estimations to be performed in the time domain.In addition to tracking the frequency of the wheels, the accelerometers are usedto track fast speed variations and detect stand still. Compared to inertial navigationwhich has a cubic positioning drift over time, this setup limits the drift to belinear in time. The proposed inertial navigation system is evaluated on datasetsrecorded in a proof of concept environment, performing continuous frequencytracking with a low average error rate. / <p>Osäker på det här med "Presentation". Den ägde rum innan detta publicerande.</p><p>Men skrev i när det skedde i alla fall.</p>

This thesis aims to examine the potential to optimize the energyusage of a building by implementing a controller that considerweather forecasts in the surrounding area.By 2040 Sweden aims to achieve 100% renewable energy production. Inaddition to implementing renewable production sources to reach thisgoal, there is a need for increased efficiency in both power andenergy consumption.Weather forecast control as a concept is designed to optimize theenergy usage of a building and thus making it more efficient. Bybuilding a weather forecast control in MATLAB and modeling abuilding in IDA Indoor Climate and Energy, the effects of thecontroller could be examined. To evaluate how the control effectsthe building and which potential there is to optimize the building,two parameters where chosen for evaluation. The parameters were howthe energy use was affected by implementing the weather forecastcontrol in the building and what potential there was to improve andchange the load profile of the building to avoid power peaks.It was found that by implementing the weather control, the energyusage of the building decreased by about 15%. On the other hand,the potential to avoid power peaks in the building was foundlimited. This limitation was because of the strong effects coldtemperatures had on the building. In conclusion, it can be statedthat a weather forecast control can be considered a goodalternative for projects focusing on energy efficiency. However,its ability to affect power peaks should be considered limited.

As development in sensor technology, situation awareness systems, and computational hardware for vehicle systems progress, an opportunity for more advanced and sophisticated vehicle safety-systems arises. With the increased level of available information---such as position on the road, road curvature and knowledge about surrounding obstacles---future systems could be seen utilizing more advanced controls, exploiting at-the-limit behavior of the vehicle. Having this in mind, optimization methods have emerged as a powerful tool for offline vehicle-performance evaluation, providing inspiration to new control strategies, and by direct implementation in on-board systems. This will, however, require a careful choice of modeling and objectives, since the solution to the optimization problem will rely on this. With emphasis on vehicle modeling for optimization-based maneuvering applications, a vehicle-dynamics testbed has been developed. Using this vehicle in a series of experiments, most extensively in a double lane-change maneuver, verified the functionality and capability of the equipment. Further, a comparative study was performed, considering vehicle models based on the single-track model, extended with, e.g., tire-force saturation, tire-force lag and roll dynamics. The ability to predict vehicle behavior was evaluated against measurement data from the vehicle testbed. A platform for solving vehicle-maneuvering optimization-problems has been developed, with state-of-the-art optimization tools, such as JModelica.org and Ipopt. This platform is utilized for studies concerning the influence different vehicle-model configurations have on the solution to critical maneuvering problems. In particular, different tire modeling approaches, as well as vehicle-chassis models of various complexity, are investigated. Also, the influence different road-surface conditions-e.g., asphalt, snow and ice-have on the solution to time-optimal maneuvers is studied. The results show that even for less complex models-such as a single-track model with a Magic Formula based tire-model-accurate predictions can be obtained when compared to measurement data. The general observation regarding vehicle modeling for the time-critical maneuvers is similar; even the least complex models can be seen to capture certain characteristics analogous to those of higher complexity. Analyzing the results from the optimization problems, it is seen that the overall dynamics, such as resultant forces and yaw moment, obtained for different model configurations, correlates very well. For different road surfaces, the solutions will of course differ due to the various levels of tire-forces being possible to realize. However, remarkably similar vehicle paths are obtained, regardless of surface. These are valuable observations, since they imply that models of less complexity could be utilized in future on-board optimization-algorithms, to generate, e.g., yaw moment and vehicle paths. In combination with additional information from enhanced situation-awareness systems, this enables more advanced safety-systems to be considered for future vehicles.

Semi-active suspension systems has become an increasingly popular alternative to the passive suspensions in recent time. By varying the spring stiffness and damping coefficient in the system, different characteristics can be achieved depending on driver preferability and road disturbances. The difference in damping coefficient will however lead to a trade-off between comfort and road holding,which means that in order to improve one of the areas, performance in the other will need to be reduced. This trade-off will also be different depending on the underlying road disturbances. This thesis is conducted on behalf of Volvo Cars, who are looking for a strategy in order to analyze the trade-off for different ISO classified roads which has been done through a literature study, theoretical analysis and comparison of control methods for different roads. A skyhook based controller was built with added modifications in order to reduce the jerk in the vehicle. Tests with the controller were carried out on a quarter car model as well as a full car model in IPG Carmaker. The simulations with the quarter car model showed that the controllerimproved the peak jerk values as well as the comfort, compared to both skyhook control and passive suspension. The full car simulations consisted of test runs on four roads, all with different road profiles and frequency content. For each road, tests were conducted with two different damper control methods as well as with a varying spring stiffness.The tested damper control methods were force gain control, which modulates the force request from the skyhook controller, as well as rate limitation control, which modulates the rate at which current is applied to the damper. The results showed that the trade-off between road holding and comfort appeared differently when the road profile changed. All results were compared to Janeway’s comfort criterion in order to validate the comfort of the vehicle. The outcome of the thesis was a strategy that involved various tuning for the semi-active damper and air suspension depending on the primary and secondary ride nature of the road. More specifically, a stiff damping is preferred during general primary ride conditions and a soft damping is preferred during general secondary ride conditions. For cases when the low frequency disturbances are small, the trade-off will be small and comfort can be improved with little to no cost of road holding. When the high frequency disturbances increase in amplitude, the damper should be tuned depending on preferability. For improved road holding ability, a stiff damping is preferred and for improved comfort, a soft damping is preferred. A soft spring will, for most cases, be preferred in terms of both road holding and comfort.

In the last decades, the development of self-driving vehicles has rapidly increased. Improvements in algorithms, as well as sensor and computing hardware have led to self-driving technologies becoming a reality. It is a technology with the potential to radically change how society interacts with transportation. One crucial part of a self-driving vehicle is control schemes that can safely control the vehicle during evasive maneuvers. This work investigates the modeling and lateral control of tractor-trailer vehicles during aggressive maneuvers. Models of various complexity are used, ranging from simple kinematic models to complex dynamic models, which model tire slip and suspension dynamics. The models are evaluated in simulations using TruckMaker, which is a high fidelity vehicle simulator. Several lateral controllers are proposed based on Model predictive control (MPC) and linear-quadratic (LQ) control techniques. The controllers use different complex prediction models and are designed to minimize the path-following error with respect to a geometric reference path. Their performance is evaluated on double lane change maneuvers of various lengths and with different longitudinal speeds. Additionally, the controllers' robustness against changes in trailer mass, weight distribution, and road traction is investigated. Extensive simulations show that dynamic prediction models are necessary to keep the control errors small when performing maneuvers that result in large lateral accelerations. Furthermore, to safely control the tractor-trailer vehicle during high speeds, it is a necessity to include a model of the trailer dynamics. The simulation study also shows that the proposed LQ controllers have trouble to evenly balance tractor and trailer deviation from the path, while the MPC controllers handle it much better. Additionally, a method for approximately weighting the trailer deviation is shown to improve the performance of both the LQ and MPC controllers. Finally, it is concluded that an MPC controller with a dynamic tractor-trailer model is robust against model errors, and can become even more robust by tuning the controller weights conservatively.