Miniature air vehicles (MAVs) are particularly well suited for short-distance, over-the-horizon, low-altitude surveillance and reconnaissance tasks. New camera and battery technologies have greatly increased a MAVs potential for these tasks. This thesis focuses on aerial surveillance of borders and roads, where a strap-down camera is used in-the-loop to track a border or road pathway. It is assumed that quality tracking requires that the pathway always remain in the footprint of the camera. The objective of this thesis is to explore roll-angle and altitude-above-ground-level constraints imposed on a bank-to-turn MAV due to the requirement to keep the pathway in the footprint of a downward-looking strap-down camera. This thesis derives the required altitude to maintain the pathway in the footprint of the camera and associated bank-angle constraints. Constraints are derived for both roads whose geometry is unknown a priori and roads with known geometry obtained from digital elevation map (DEM) data. MAV geometry and camera localization are used to derive these constraints. The thesis also discusses simple computer vision techniques for pathway following and a corresponding guidance law. The pixels of the captured color video are statistically classified into road and non-road components. Standard computer vision functions are used to eliminate classification noise and obtain a road heading direction. The effectiveness of the result is explored using a high fidelity simulator. Flight test results on small UAVs demonstrate the practicality of the road-following method.

Utilizing the Euler-Rodrigues symmetric parameters (attitude quaternion) to describe vehicle orientation, we develop a multiplicative, nonlinear (extended) variation of the Kalman filter (MEKF) to fuse data from low-cost sensors. The sensor suite is comprised of gyroscopes, accelerometers, and a GPS receiver. In contrast to the common approach of using the complete vehicle attitude as the quantities to be estimated, our filter states consist of the three components of an attitude error vector. In parallel with the time update of the attitude error estimate, we utilize the gyroscope measurements for the time propagation of the attitude quaternion. The accelerometer and the GPS sensors are used independently for the measurement update portion of the Kalman filter. For both sensors, a vector arithmetic approach is used to determine the attitude error vector. Following each measurement update, a multiplicative reset operation moves the attitude error information from the filter state into the attitude estimate. This reset operation utilizes quaternion algebra to implicitly maintain the unity-norm constraint. We demonstrate the effectiveness of our attitude estimation algorithm through flight simulations and flight tests of aggressive maneuvers such as loops and small-radius circles. We implement an approach to aerobatic maneuvering for miniature air vehicles (MAVs) using time-parameterized attitude trajectory generation and an associated attitude tracking control law. We designed two methodologies, polynomial and trigonometric, for creating functions that specify pitch and roll angles as a function of time. For both approaches, the functions are constrained by the maneuver boundary conditions of aircraft position and velocity. We construct a trajectory tracking feedback control law to regulate aircraft orientation throughout the maneuvers. The trajectory generation algorithm was used to construct several maneuvers and trajectory tracking control law successfully executed the maneuvers in the flight simulator. In addition to the simulation results, MAV flight tests verified the performance of the maneuver generation and control. To achieve obstacle avoidance maneuvering, the time parameterized trajectories were converted to spatially parameterized paths, which allowed for inertial reference frame position error to be included in the control law feedback loop. We develop a novel method to achieve the spatial parameterization using a prediction and correction approach. Additionally, the first derivative of position of the desired path is modified using a corrective parameter scheme prior to being used in the control. Using the path position error and the corrected derivative, we utilize a unit-norm quaternion framework to implement a proportional-derivative (PD) control law. This control law was demonstrated in simulation and hardware on maneuvers designed specifically to avoid obstacles, namely the Immelmann and the Close-Q, as well as a basic loop.

Applications such as urban surveillance, search and rescue, agricultural applications, military applications, etc., require miniature air vehicles (MAVs) to fly for a long time. But they have restricted flight duration due to their dependence on battery life, which necessitates optimal path planning. The generated optimal path should obey the curvature limits prescribed by the minimum turn radius/ maximum turn rate of the MAV. Further, in a dynamically changing environment, the final configuration that the MAV has to achieve may change en route, which demands the path to be replanned by an airborne processor in real-time. As MAVs are small in size and light in weight, wind has a very significant effect on the flight of MAVs and the computation of the minimum-time path in the presence of wind plays an important role. The thesis develops feasible trajectory generation algorithms which are fast, efficient, optimal and implementable in an onboard computer for rectilinear and circular path convergence problems and waypoint following problems both in the absence and in the presence of wind. The first part of the thesis addresses the problem of computation of optimal trajectories when MAVs fly on a two-dimensional (2D) plane maintaining a constant altitude. The shortest path is computed for MAVs from a given initial position and orientation to a given final path with a specified direction as required for a given mission. Unlike the classical Dubins problem where the shortest path was computed between two given configurations (position and orientation), the final point in this case is not specified. However, the final path, which can either be a rectilinear path or a circular path, and the direction to which the MAV should converge, is specified. The time-optimal path of MAVs is developed in the presence of wind mainly using the geometric approach although a few important properties are also obtained using optimal control theory, specifically, Pontryagin’s minimum principle (which provides only the necessary condition for optimality) for control-constrained systems. The complete optima l solution to this problem in all its generality is a major contribution of this thesis as existing methods in the literature that address this problem are either not optimal or do not give a complete solution. Further, the time-optimal path for specified initial and final configurations is generated in reasonably short time without computing all the path lengths of possible candidate paths, which is the method that exists in the literature for similar problems. Simulation results illustrate path generation for various cases, including the presence of steady and time-varying wind. Another problem in MAV path planning in 2D addressed in this thesis computes an extremal path that transitions between two consecutive waypoint segments (obtained by joining two way points in sequence) in a time-optimal fashion. This designed trajectory, named as γ-trajectory, is also used to track the maximum portion of waypoint segments in minimum time and the shortest distance between this trajectory and the associated waypoint can be set to a desired value. Another optimal path, called the loop trajectory, that goes through the way points as well as through the entire waypoint segments, is also proposed. Subsequently, the thesis proposes algorithms to generate trajectories in the presence of steady wind and compares these with the optimal trajectory generated using nonlinear programming based multiple shooting method to show that the generated paths are optimal in most cases. In three-dimensional (3D) space, if the initial and final configurations – in terms of (X,Y,Z) position, heading angle and flight path angle- of the vehicle are specified then shortest path computation is an interesting problem in literature. The proposed method in this thesis is based on 3D geometry and, unlike the existing iterative methods which yield suboptimal paths and are computationally more intensive, this method generates the shortest path in much less time. Due to its simplicity and low computational requirements, this approach can be implemented on a MAV in real-time. But, If the path demands very high pitch angle (as in the case of steep climbs), the generated path may not be flyable for an aerial vehicle with limited range of flight path angles. In such cases numerical methods, such as multiple shooting, coupled with nonlinear programming, are used to obtain the optimal solution. The time-optimal 3D path is also developed in the presence of wind which has a magnitude comparable to the speed of MAVs. The simulation results show path generation for a few sample cases to show the efficacy of the proposed approach as compared to the available approach in the literature. Next, the path convergence problem is studied in 3D for MAVs. The shortest path is generated to converge to a rectilinear path and a circular path starting from a known initial position and orientation. The method is also extended to compute the time-optimal path in the presence of wind. In simulation, optimal paths are generated for a variety of cases to show the efficacy of the algorithm. The other problem discussed in this thesis considers curvature-constrained trajectory generation technique for following a series of way points in 3D space. Extending the idea used in 2D, a γ-trajectory in 3D is generated to track the maximum portion of waypoint segments with a desired shortest distance between the trajectory and the associated waypoint. Considering the flyability issue of the plane a loop-trajectory is generated which is flyable by a MAV with constrained flight path angle. Simulation results are given for illustrative purposes. The path generation algorithms are all based on a kinematic model, considering the vehicle as a point in space. Implementing these results in a real MAV will require the dynamics of the MAV to be considered. So, a 6-DOF SIMULINK model of a MAV is used to demonstrate the tracking of the computed paths both in 2D plane and in 3D space using autopilots consisting of proportional-integral-derivative (PID )controllers .Achieving terminal condition accurately in real-time, if there is noisy measurement of wind data, is also addressed.