# Special Issue on Unmanned Aerial Vehicles (UAVs)
## 2 Advanced UAV Technologies  
Unmanned Aerial Vehicle (UAV) services such as sensing, mapping, goods and equipment delivery, inspection, and monitoring have started to proliferate with the rapidly falling prices of both drones and the sensors mounted on them. Many of these services involve the gathering of data and its processing with complex algorithms either in real-time or on the cloud, and precise navigation and path-planning of the drones. Most of these applications are performed by single UAVs till now, though the use of a multiplicity of UAVs can significantly improve performance. This special issue was introduced to collect the latest research on relevant topics, and more importantly, to address challenging present problems with all areas of technologies related to UAVs. There were 50 papers submitted to the special issue, and 26 papers were accepted (i.e., 52% acceptance rate). When looking back to the special issues, various topics have been addressed, mainly on communication (two papers), control (eight papers), collision avoidance (one paper), modeling (one paper), path planning (six papers), human-machine interface (HMI) (one paper), artificial intelligence (AI) (three papers), etc (four papers). There are two papers focused on UAV communication technology [1,2]. [PERSON], [PERSON], and [PERSON] present the risk assessment on autonomous vehicular V2V communication [1]. [PERSON], [PERSON], [PERSON], and [PERSON] present an adaptive TCP transmission adjustment technique for the robust UAV communication network build-up [2]. There are eight papers focused on UAV control technology [3, 4, 5, 6, 7, 8, 9, 10]. [PERSON], [PERSON], and [PERSON] present plasma actuators were introduced to simplify the complex feathering motion and to control the flow around insect's flapping wings having simplified sinusoidal motion [3]. [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] propose an integrated robust adaptive Kalman filter, called the strong adaptive Kalman filter (SAKF), to solve the divergence and low accuracy issues of the existing Kalman filter (KF) for the high-speed UAV application [4]. [PERSON] and [PERSON] present an interacting multiple model (IMM) filtering based empirical method to detect and track moving pedestrians using a small UAV (SUAV) in which the detection algorithm is consisted of frame subtraction, thresholding, morphological filter, and false alarm reduction processes and the tracking algorithm uses the output from the detection algorithm processes [5]. [PERSON], [PERSON], and [PERSON] present a step by step empirical processes for the adaptive trajectory tracking control of SUAV, in particular, by using the Euler-Lagrange based backstepping control technique [6]. [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] present a lateral-directional control method for the high aspect ratio full-wing UAV without any aileron and rudder using the differential thrust of propellers as the control output and the yaw angle as the controlled attitude angle [7]. [PERSON], [PERSON], and [PERSON] present a direct visual servoing system for the UAV using a single onboard high-speed monocular camera to accomplish the autonomous flight in GPS denied area [8]. [PERSON] and [PERSON] present a robust backstepping trajectory control of the SUAV based on both the parameterized uncertainties and external disturbances by solving the control input saturation issue with a new auxiliary system [9]. [PERSON], [PERSON] and [PERSON] present an adaptive neural fault-tolerant tracking control scheme for the yaw control of the multicopter type UAV, which is a non-affine nonlinear system, to manage actuator faults, input saturation, full-state constraints, and external disturbances [10]. There is one paper focused on UAV collision avoidance technology [11]. [PERSON], [PERSON], and [PERSON] present a collision avoidance (CA) algorithm for a cooperative fixed-wing UAV based on the maneuver coordination and planned trajectory prediction by generating and predicting three trajectory candidates [11].