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Multicopters are important tools in industry, the military, and research but suffer from short flight times and mission durations. In this thesis, we discuss three different ways to increase flight times and therefore increase the viability of using multicopters in a variety of missions. Alternate fuel sources such as hydrogen fuel and solar cells are starting to be used on multicopters, in our research we simulate modern fuel cells and show how well they currently work as the power source for multicopters and how close they are to becoming useful in Unmanned Aircraft System (UAS) technology. Increasing the efficiency in which the available energy is used can also increase mission duration. Two characteristics that affect the efficiency of a mission are the flight speeds of the multicopter and the payload it carries. These characteristics are well known in larger rotorcrafts but often ignored in smaller multicopters. In our research, we explore the effect of flight speed on the dynamics of a multicopter and show that higher speeds lead to higher flight times due to the effect of translational lift. Lastly, we developed an online updating multi-flight planning algorithm for stop and charge missions, a method that can potentially indefinitely extend a mission. The multi-flight planning algorithm, the variable resolution horizon, reduces the computing resources necessary to 15% to 40% of a typical optimal planner while having a maximum 5.6% decrease in expected future reward, a metric for accuracy. The results of this thesis help guide decisions in fuel type for multicopter missions show examples of how to increase flight time through increasing efficiency and develop the framework for multi-flight missions. Advisers: Justin Bradley and Carrick Detweiler

Multicopter aircrafts have become popular platforms for researching flight control and aerial image processing applications. These crafts could gain unique utility from the ability to fly to remote locations, land, then walk to perform close quarters inspection of the area. This thesis presents a novel hexapod-quadcopter design with multicopter flight hardware directly embedded in the hexapod legs. The robot was assembled from custom designed 3D printed structural components. Software was developed for the walking and flying locomotion methods as well as transitional procedures necessary to switch between these two modes. The robot functionality was tested and validated to work on the platform.

An Unmanned Air Vehicle (UAV) is an aircraft without a human pilot on board. It can be controlled either autonomously by computers onboard, or using a remote control by a pilot on the ground, or in another vehicle. In both military and civilian sectors, UAVs are quickly obtaining popularity and expected to expand dramatically in the years to come. As UAVs gain more attention, one of the immediate requirements would be to have UAVs work as much autonomously as possible. One of the common tasks that UAVs would be engaged in is target tracking which has various potential applications in military field, law-enforcement, wildlife protection effort, and so on.This thesis focuses on development of a controller for UAVs to track ground target. In particular, this thesis focuses on quadrotor UAV, which is a multicopter that is lifted and propelled using four motors. Admittedly, several target tracking control methods have been developed in recent years. However, only a few of them have been applied on a quadrotor. Most of these tracking methods, particularly those based on Proportional Derivative (PD) control laws, which have been applied on quadrotors, are not time efficient due to practical acceleration constraint and a number of parameters that need to be tuned. The UAV control problem can be divided into 4 sub-problems: Position Control, Motor Control, Trajectory Tracking and Trajectory Generation. In this thesis, the dynamic equations of motion for quadrotors and a Proportional Derivative control law is derived to solve the problems of Position Control, Motor Control and Trajectory Tracking. A Proportional Navigation (PN) based switching strategy is proposed to address the problem of Trajectory Generation. The experiments and numerical simulations are performed using non-maneuvering and maneuvering targets. The simulation results show that the proposed PN based switching strategy not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method.The switching strategy, as proposed as a solution to target tracking problem, leaves an important question with regard to when should the switching happen. It is intuitive that the time of switching will play a role in how fast the UAV converges to the target. The second problem considered in this thesis relates to the optimal time of switching that would minimize the positional error between the UAV and the target. An optimal switching strategy is proposed to obtain the optimal switching time for both non-maneuvering and maneuvering targets. Analytical solutions that generate trajectories based on PN and PD methods are used in this strategy. The numerical simulations validate the optimality, reliability, and accuracy of the proposed method for both non-maneuvering and maneuvering targets.