Real-Time Navigation, Guidance, and Control of a UAV Using Low-Cost Sensors
نویسندگان
چکیده
Applying low-cost sensors for the Guidance, Navigation and Control (GNC) of an autonomous Uninhibited Aerial Vehicle (UAV) is an extremely challenging area. This paper presents the real-time results of applying a low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) receiver for the GNC. The INS/GPS navigation loop provides continuous and reliable navigation solutions to the guidance and flight control loop for autonomous flight. With additional air data and engine thrust data, the guidance loop computes the guidance demands to follow way-point scenarios. The flight control loop generates actuator signals for the control surfaces and thrust vector. The whole GNC algorithm was implemented within an embedded flight control computer. The real-time flight test results show that the vehicle can perform the autonomous flight reliably even under high maneuvering scenarios.
منابع مشابه
Low Cost UAV-based Remote Sensing for Autonomous Wildlife Monitoring
In recent years, developments in unmanned aerial vehicles, lightweight on-board computers, and low-cost thermal imaging sensors offer a new opportunity for wildlife monitoring. In contrast with traditional methods now surveying endangered species to obtain population and location has become more cost-effective and least time-consuming. In this paper, a low-cost UAV-based remote sensing platform...
متن کاملGPS Jamming Detection in UAV Navigation Using Visual Odometry and HOD Trajectory Descriptor
Auto-navigating of unmanned aerial vehicles (UAV) in the outdoor environment is performed by using the Global positioning system (GPS) receiver. The power of the GPS signal on the earth surface is very low. This can affect the performance of GPS receivers in the environments contaminated with the other source of radio frequency interference (RFI). GPS jamming and spoofing are the most serious a...
متن کاملCalibration of an Inertial Accelerometer using Trained Neural Network by Levenberg-Marquardt Algorithm for Vehicle Navigation
The designing of advanced driver assistance systems and autonomous vehicles needs measurement of dynamical variations of vehicle, such as acceleration, velocity and yaw rate. Designed adaptive controllers to control lateral and longitudinal vehicle dynamics are based on the measured variables. Inertial MEMS-based sensors have some benefits including low price and low consumption that make them ...
متن کاملReal-Time Attitude and Position Estimation for Small UAVs Using Low-Cost Sensors
Small unmanned air vehicles (UAVs) and micro air vehicles (MAVs) have payload and power constraints that prohibit heavy sensors and powerful processors. This paper presents real-time attitude and position estimation solutions that use small, inexpensive sensors and low-power microprocessors. In connection with an Extended Kalman Filter attitude estimation scheme, a novel method for dealing with...
متن کاملAdaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors
Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper p...
متن کامل