<p>Automated Vehicle Path Following Control (PFC) is an advanced control system that can regulate the vehicle into a collision-free region in the presence of other objects on the road. Common collision avoidance functions, such as forward collision warning and automatic emergency braking, have recently been developed and equipped on production vehicles. However, it is impossible to develop a perfectly precise vehicle model when the vehicle is driving. The most PFC did not consider uncertainties in the vehicle model, external disturbances, and parameter variations at the same time. To address the issues associated with this important feature and function in autonomous driving, a new vehicle PFC is proposed using a robust model predictive control (MPC) design technique based on matrix inequality and the theoretical approach of the hybrid $\&$ switched system. The proposed methodology requires a combination of continuous and discrete states, e.g. regulating the continuous states of the AV (e.g., velocity and yaw angle) and discrete switching of the control strategy that affects the dynamic behaviors of the AV under different driving speeds. Firstly, considering bounded model uncertainties, norm-bounded external disturbances, the system states and control matrices are modified. In addition, the vehicle time-varying longitudinal speed is considered, and a vehicle lateral dynamic model based on Linear Parameter Varying (LPV) is established by utilizing a polytope with finite vertices. Then the Min-Max robust MPC state feedback control law is obtained at every timestamp by solving a set of matrix inequalities which are derived from Lyapunov stability and the minimization of the worst-case in infinite-horizon quadratic objective function. Compared to adaptive MPC, nonlinear MPC, and cascade LPV control, the proposed robust LPV MPC shows improved tracing accuracy along vehicle lateral dynamics. Finally, the state feedback switched LPV control theory with separate Lyapunov functions under both arbitrary switching and average-dwell-time (ADT) switching conditions are studied and applied to cover the path following control in full speed range. Numerical examples, tracking effectiveness, and convergence analysis are provided to demonstrate and ensure the control effectiveness and strong robustness of the proposed algorithms.</p>

This thesis describes the current state of development of the Flexible Low-cost Automated Scaled Highway (FLASH) laboratory at the Virginia Tech Transportation Institute (VTTI). The FLASH lab and the scale model cars contained therein provide a testbed for the small scale development stage of intelligent transportation systems (ITS). In addition, the FLASH lab serves as a home to the prototype display being developed for an educational museum exhibit. This thesis also gives details of the path following lateral controller implemented on the FLASH car. The controller was developed using the kinematic model for a wheeled robot. The global model is converted into the path coordinate model so that only local variables are needed. then the path coordinate model is converted into chained form and a controller is given to perform path following. The path coordinate model introduces a new parameter to the system: the curvature of the path. Thus, it is necessary to provide the path's curvature value to the controller. Because of the environment in which the car is operating, the curvature values are known a priori. Several online methods for determining the curvature are developed. A MATLAB simulation environment was created with which to test the above algorithms. The simulation uses the kinematic model to show the car's behavior and implements the sensors and controller as closely as possible to the actual system. The implementation of the lateral controller in hardware is discussed. The vehicle platform is described and the harware and software architecture detailed. The car described is capable of operating manually and autonomously. In autonomous mode, several sensors are utilized including: infrared, magnetic, ultrasound, and image based technology. The operation of each sensor type is described and the information received by the processor from each is discussed. / Master of Science

Quadrotors, being more agile than fixed-wing vehicles, are the ideal candidates for autonomous missions in small, compact spaces. The immense challenge to navigate such environments is fulfilled by the concept of path following. Path following is the method of tracking/tracing a fixed, pre-defined path with minimum position error while exerting the lowest possible control effort. In this work, the missile guidance technique of pure pursuit is adopted and modified for a 3D quadrotor model to follow fixed, compact trajectories. A specialized hardware testing platform is developed to test this algorithm. The results obtained from simulation and flight tests are compared to results from another technique called differential flatness. A small part of this thesis also deals with the stability analysis of the modified 3D pure pursuit algorithm to track trajectories expending lower control effort.

付記する学位プログラム名: デザイン学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21761号 / 工博第4578号 / 新制||工||1713(附属図書館) / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 藤本 健治, 教授 泉田 啓, 教授 太田 快人 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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The navigation and control of an autonomous vehicle is a highly complex task. Making a vehicle intelligent and able to operate "unmanned" requires extensive theoretical as well as practical knowledge. An autonomous vehicle must be able to make decisions and respond to situations completely on its own. Navigation and control serves as the major limitation of the overall performance, accuracy and robustness of an autonomous vehicle. This thesis will address this problem and propose a unique navigation and control scheme for an autonomous lawn mower (ALM). Navigation is a key aspect when designing an autonomous vehicle. An autonomous vehicle must be able to sense its location, navigate its way toward its destination, and avoid obstacles it encounters. Since this thesis attempts to automate the lawn mowing process, it will present a navigational algorithm that covers a bounded region in a systematic way, while avoiding obstacles. This algorithm has many applications including search and rescue, floor cleaning, and lawn mowing. Furthermore, the robustness and utility of this algorithm is demonstrated in a 3D simulation. This thesis will specifically study the dynamics of a two-wheeled differential drive vehicle. Using this dynamic model, various control techniques can then be applied to control the movement of the vehicle. This thesis will consider both open loop and closed loop control schemes. Optimal control, path following, and trajectory tracking are all considered, simulated, and evaluated as practical solutions for control of an ALM. To design and build an autonomous vehicle requires the integration of many sensors, actuators, and controllers. Software serves as the glue to fuse all these devices together. This thesis will suggest various sensors and actuators that could be used to physically implement an ALM. This thesis will also describe the operation of each sensor and actuator, present the software used to control the system, and discuss physical limitations and constraints that might be encountered while building an ALM. / Master of Science

There are many applications for which small unmanned aerial vehicles (SUAVs) are well suited, including surveillance, reconnaissance, search and rescue, convoy support, and short-range low-altitude perimeter patrol missions. As technologies for microcontrollers and small sensors have improved, so have the capabilities of SUAVs. These improvements in SUAV performance increase the possibility for hazardous missions through mountainous and urban terrain in the successful completion of many of these missions. The focus of this research was on remote terrain navigation and the issues faced when dealing with limited onboard processing and limited payload and power capabilities. Additional challenges associated with canyon and urban navigation missions included reactive path following, sensor noise, and flight test design and execution. The main challenge was for an SUAV to successfully navigate through a mountainous canyon by reactively altering its own preplanned path to avoid canyon walls and other stationary obstacles. A robust path following method for SUAVs that uses a vector field approach to track functionally curved paths is presented along with flight test results. In these results, the average tracking error for an SUAV following a variety of curved paths is 3.4~m for amplitudes ranging between 10 and 100~m and spatial periods between 125 and 500~m. Additionally, a reactive path following method is presented that allows a UAV to continually offset or bias its planned path as distance information from the left and right ranging sensors is computed. This allows the UAV to to center itself between potential hazards even with imperfect waypoint path planning. Flight results of an SUAV reactively navigating through mountainous canyons experimentally verify the feasibility of this approach. In a flight test through Goshen Canyon in central Utah, an SUAV biased its planned path by 3 to 10~m to the right as it flew to center itself through the canyon and avoid the possibility of crashing into a canyon wall.

In this thesis we develop methods that facilitate an aerial rendezvous between two air vehicles. The objective of this research is to produce a method that can be used to insert a miniature air vehicle behind a rendezvous vehicle and then track that vehicle to enable a visual rendezvous. For this research we assume the rendezvous vehicle is following a relatively stable and roughly elliptical orbit. Path planners and controllers have been developed that can be used to effectively intercept the rendezvous vehicle by inserting the MAV onto the orbit of interest. A method for planning and following time-optimal Dubins airplane interception paths between a miniature air vehicle and the rendezvous vehicle is presented. We demonstrate how a vector field path following a scheme can be used for navigation along these time-optimal Dubins airplane paths. A post-orbit insertion tracking method is also presented which can be used to track the target vehicle on an arbitrarily oriented elliptical orbit while maintaining a specified following distance. We also present controllers that can be used for disturbance rejection during the orbit-insertion and interception operations. All of these methods were implemented in simulation and with hardware. Results from these implementations are presented and analyzed.

The objective of this thesis is to analyze the kinematics of a mobile parallel robot with contribution that pertain to the singularity analysis, the optimization of geometric parameters and the optimal control to avoid singularities when navigating across singular geometric configurations. The analysis of the workspace and singularities is performed in a prescribed reference workspace regions using discretization method. Serial and parallel singularities are analytically analyzed and all possible singular configurations are presented. Kinematic conditioning index is used to determine the robot’s proximity to a singular configuration. A method for the determination of a continuous and singularity-free workspace is detailed. The geometric parameters of the system are optimized in various types of pipe-like structures with respect to a suitable singularity index, in order to avoid singularities during the navigation across elbows. The optimization problem is formulated with an objective to maximize the reachable workspace and minimize the singularities. The objective function is also subjected to constraints such as collision avoidance, singularity avoidance, workspace continuity and contact constraints imposed between the boundaries and the wheels of the robot. A parametric variation method is used as a technique to optimize the design parameters. The optimal design parameters found are normalized with respect to the width of the pipe-like structures and therefore the results are generalized to be used in the development phase of the robot. An optimal control to generate singularity-free trajectories when the robotic device has to cross a geometric singularity in a sharp 90◦ elbow is proposed. Such geometric singularity inherently leads to singularities in the Jacobian of the system, and therefore a modified device with augmented number of degrees of freedom is introduced to be able to generate non-singular trajectories.

The objective of this thesis is to analyze the kinematics of a mobile parallel robot with contribution that pertain to the singularity analysis, the optimization of geometric parameters and the optimal control to avoid singularities when navigating across singular geometric configurations. The analysis of the workspace and singularities is performed in a prescribed reference workspace regions using discretization method. Serial and parallel singularities are analytically analyzed and all possible singular configurations are presented. Kinematic conditioning index is used to determine the robot’s proximity to a singular configuration. A method for the determination of a continuous and singularity-free workspace is detailed. The geometric parameters of the system are optimized in various types of pipe-like structures with respect to a suitable singularity index, in order to avoid singularities during the navigation across elbows. The optimization problem is formulated with an objective to maximize the reachable workspace and minimize the singularities. The objective function is also subjected to constraints such as collision avoidance, singularity avoidance, workspace continuity and contact constraints imposed between the boundaries and the wheels of the robot. A parametric variation method is used as a technique to optimize the design parameters. The optimal design parameters found are normalized with respect to the width of the pipe-like structures and therefore the results are generalized to be used in the development phase of the robot. An optimal control to generate singularity-free trajectories when the robotic device has to cross a geometric singularity in a sharp 90◦ elbow is proposed. Such geometric singularity inherently leads to singularities in the Jacobian of the system, and therefore a modified device with augmented number of degrees of freedom is introduced to be able to generate non-singular trajectories.