Using Roads for Autonomous Air Vehicle Guidance

Abstract

This is a study on the development of a road following vision-based guidance system for unmanned air vehicles (UAV) in real world applications. Currently, autonomous navigation requires the use of GPS. In many applications, however, dependence on GPS is undesirable. GPS signals are weak and can be jammed easily. Also, GPS waypoints may not be up-to-date. In recent years, vision-based navigation has been gaining popularity. Vision-based guidance requires existence of visible paths or extended landmarks for air vehicles to detect and follow. Roads are the most commonly available path to follow. Moreover, the abundance of events that happen along roads make them appealing subjects of surveillance. Many road detection (single images) and road tracking (videos) algorithms have been proposed in the literature. Fast detection and tracking has been the emphasis of those intended for UAVs. Due to the complexity of road detection, we not only need advanced software but also the most effective sensors. In this paper, we propose a road following algorithm that uses both RGB camera and hyperspectral sensor and report the results of actual test flights conducted in different locations and different seasons.

Moving target tracking method for unmanned aerial vehicle/unmanned ground vehicle heterogeneous system based on AprilTags

“…30 It is a visual reference library 31 and widely used in robots and UAV positioning guide. 32 AprilTag uses a simple Quick Response code (QR code) which has only 4- to 12-bit data and can be detected more robustly and from longer ranges.…”

An Integrated Scheme of a Smart Net Capturer for MUAVs

“…The function of guidance subsystem is to measure the relative position and relative speed between the guided weapon and the target, to calculate the deviation of the actual flight trajectory from the theoretical trajectory, to give a correction signal deviation, and then to deliver it to the control system. The function of the control subsystem is to adjust the movement or posture of the guided weapon according to the correction signal output by the guidance subsystem for changing the missile trajectory, so the guided weapon can accurately fly to the target [10], [11]. The schematic diagram of the aircraft technology using guidance control technology is shown in Figure 1.…”

Saliency-enhanced background-aware correlation filters with dual temporal regularization for unmanned aerial vehicle tracking

“…Currently, its application to unmanned aerial vehicles (UAVs) has become a research hotspot and received considerable attention in the CV domain. An increasing number of applicants has emerged, such as target and path following, 1 , 2 autonomous landing, 3 , 4 air surveillance, 5 and collision avoidance 6 . Despite the plethora of visual tracking methods that have been designed for UAV applications, 7 it is still a challenging task to achieve accurate and robust tracking, especially in complex scenarios.…”