• Visual Servo Control
• Pose Estimation
• Inter-Process Communication
• Real-Time Image Acquisition

This thesis describes the design of a Real Time Machine-Vision (MV) Position Sensing System for the problem of Semi-Autonomous Docking within Aerial Refueling (AR) for Unmanned Aerial Vehicles (UAVs). MV-based algorithms are implemented within the proposed scheme to detect the relative position and orientation between the UAV and the tanker.
In this effort, techniques and algorithms for the acquisition of the image from a real Webcam, for the Feature Extraction (FE) from the acquired image, for the Detection and Labeling (DAL) of the features, for the tanker-UAV Pose Estimation (PE) have been developed and extensively tested in MATLAB/Simulink® Soft Real-Time environment and in Linux/RTAI Hard Real-Time environment.
Firstly it was implemented the MV block of the previous entire simulation with real videos and real images from a webcam instead of the Virtual Reality Toolbox ® visualization. After the webcam-based MV was relocated to reach the Hard Real-Time requirements.
Additionally, it’s developed a new way for the inter-process communication among Real-Time and Non Real-Time processes, implementing the Cyclic Asynchronous Buffer (CAB) on RTAI.
Finally the entire sensing system was tested using an 800Mhz PC-104 computer (the On-Board Computer embedded on the YF-22 UAV models of the WVU Laboratories), and the results confirmed the feasibility of executing image processing algorithms in real-time using off-the-shelf commercial hardware to obtain reliable relative position and orientation estimations.