Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

This paper focuses on the transition process optimization for a vertical takeoff and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV). For VTOL UAVs that can fly with either hover or cruise mode, transition refers to the intermediate phases between these two modes. This work develops a transition strategy with the trajectory optimization method. The strategy is a reference maneuver enabling the vehicle to perform transition efficiently by minimizing the cost of energy and maintaining a small change of altitude. The simplified 3-degree-of-freedom (3-DOF) longitudinal aerodynamic model is used as a dynamic constraint. The transition optimization problem is then modeled by nonlinear programming (NLP) and solved by the collocation method to obtain the reference trajectory of the pitch angle and throttle offline. Simulations with the Gazebo simulator and outdoor flight experiments are carried out with the optimized forward (hover-cruise) and backward (cruise-hover) transition solutions. The simulation and experimental results show that the optimized transition strategy enables the vehicle to finish transition with less time and change of altitude compared with that by using traditional linear transition methods.

This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs’ communication with the same relay structure.