Flight Control Board Research Articles

Arduino Based Flight Control Card Design and Quadcopter Integration

Unmanned aerial vehicles are used quite widely today, especially quadcopters, which we often encounter in areas such as the defense industry, agriculture, and civil aviation. Dec Jul Flight control cards are the products with the highest cost among these products, especially for someone who has a hobby in civilian life or who is curious about electronics and aviation, so it is quite expensive to supply or produce these vehicles. We are designing and producing a cost-effective, easily accessible, and affordable flight control card by using Arduino and Gyroscope sensors in the works we are planning. At the same time, a design is considered one in which the user can code as open-source hardware. The project has two working areas, hardware and software. The work in the hardware field involves designing the flight control board through the drawing program, producing printed circuits for the designed board, and integrating Arduino Mega and other components into this board. On the software side, it is the control algorithm and flight software coding via Arduino IDE. Due to the fact that it has a large number of libraries, it is accessible and understandable to most people, so the Arduino IDE program has been used.

UAV Control Based on Pattern Recognition in Aquaculture Application

This study proposes a drone application for the net cage aquaculture industry. A visual control structure is applied to the drone to obtain water-quality information surrounding the net cages. This study integrates a hexacopter, camera, onboard computer, flight control board, servo motor, and global positioning system’s auto-cruise function to adjust the drone position and control the servo motor retractable sensor to reach the desired target at an accurate location. In object identification, a deep learning neural network is used to identify the net cages. An onboard computer calculates the horizontal distance between the drone and the net cage. A “You only look once” (YOLO) neural network is used to detect the net cage images. Considering the hardware calculation speed and ability, an onboard computer is applied to process the flight control board and control the drone. In the mission, an aerial camera detects targets (net cage) and provides visual information to the drone for the target approaching control process. After executing the water-quality measurement, the drone will end the mission and return to the base. This study modifies the architecture of YOLO, compares it with the original model, and then finds a proper architecture for this mission. This study aims to assist cage aquaculture operators by using drones to measure water quality, which can reduce aquaculture’s labor costs.

Simultaneous arm morphing quadcopter and autonomous flight system design

Purpose The purpose of this paper is to obtain values that stabilize the lateral and longitudinal flight of the quadrotor for which the morphing amount and the best Proportional-Integral-Derivative (PID) coefficients are determined by using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm. Design/methodology/approach Quadrotor consists of body and arms; there are propellers at the ends of the arms to take off and rotors that rotate them. By reducing the angle between mechanism 1 and the rotors with the horizontal plane, the angle between mechanism 2 and the arms, the rotors rise and different configurations are obtained. Conventional multi-rotor aircraft has a fixed fuselage and does not need a tail rotor to change course as helicopters do. The translational and rotational movements are provided by the rotation of the rotors of the aircraft at different speeds by creating moments about the geometric center in 6-degree-of-freedom (DOF) space. These commands sent from the ground are provided by the flight control board in the aircraft. The longitudinal and lateral flight stability and properties of different configurations evaluated by dynamic analysis and simulations in 6 DOF spaces are investigated. An algorithm and PID controller are being developed using SPSA to achieve in-flight position and attitude control of an active deformable aircraft. The results are compared with the results of the literature review and the results of the previous article. Findings With SPSA, the best PID coefficients were obtained in case of morphing. Research limitations/implications The effects of quadrotor arm height and hub angle changes affect flight stability. With the SPSA optimization method presented in this study, the attitude is quickly stabilized. Practical implications With the optimization method, the most suitable PID coefficients and angle values for the lateral and longitudinal flight stability of the quadrotor are obtained. Social implications The transition rate and PID coefficients are determined by using the optimization method, which is advantageous in terms of cost and practicality. Originality/value With the proposed method, the aircraft can change shape to adapt to different environments, and the parameters required for more stable flight for each situation will be calculated, and this will be obtained more quickly and safely with the SPSA optimization method.

Multipurpose deep learning-powered UAV for forest fire prevention and emergency response

This paper presents a customized UAV designed for rescue and safety purposes in the forest sector. The UAV features a durable F450 frame quadcopter with four 1000KV brushless motors and a KK2.1 Flight Control Board for stability and manoeuvrability with a runtime of 90 min. It incorporates a Raspberry Pi camera for real-time video streaming, enabling efficient identification of individuals in need of assistance. The GSM module allows contactless communication, ensuring streamlined and safe interaction. A motor controls the lid of the customizable first aid kit box, facilitating efficient aid delivery. The Neo-6 M GPS module provides accurate localization of the drone and individuals in distress with a horizontal position accuracy of 2.5 m. The UAV collects temperature and humidity data using the DHT 11 sensor having +/- 2 degreesC and +- 5% accuracy respectively. This sensor employs advanced deep learning models, including artificial neural networks (ANN) and generative adversarial networks (GANs), for real-time forest fire prediction with an accuracy of 90.7 % The integration of GANs enhances accuracy through synthetic data generation. Moreover, all these components are interfaced using a Raspberry Pi4 and a GUI, providing a smooth user control experience and end-to-end information for quick and effective emergencyresponse.

Dronlarda ultrasonik sensör tabanlı engelden kaçınma sisteminin iyileştirilmesi

Although drone users have received the necessary training, the reflexes of making decisions against a sudden natural event such as wind and avoiding a nearby obstacle may not be sufficient. Therefore, whether drones fly autonomously or under user control, they must sense and act accordingly for an uninterrupted mission. In this study, a drone design and application for obstacle detection and obstacle avoidance were carried out. In the designed drone, Pixhawk was used as the flight control board, ultrasonic sensors were used to detect obstacles, and Arduino Uno was used as a microcontroller to obtain avoidance commands. The sensors used in obstacle detection and their performance are the most decisive factors in achieving the targeted goal. Because obstacle detection sensors are affected by electrical noises, the success of detecting obstacles decreases. For this reason, first of all, the integration of these sensors into the system was investigated and the drone was developed accordingly. Then, an algorithm was developed using a software filtering method both to minimize communication instabilities and to increase the clarity of detection. Finally, the ability to evade obstacles both while the drone is suspended in the air and while it is in motion has been investigated. In the experiments carried out, it was found that the drone was able to successfully avoid obstacles up to a flight speed of 3.94 m/s.

Compact Unmanned Aerial Vehicle with Carbon Fibre Frame and Propellor for Underground Application : An Approach

A drone is a device useful for surveillance, security and improve safety aspects. Drone has many applications contributing in societal developments which is the motivation for the present project work. Drone is being emerged by various military organization, commercial capacity and its applications is increasing day-by-day. Unmanned aerial vehicles are designed as a self-operating device based on receiving feedback from signals and sensors. Brushless DC motor, frames, transmitter, receiver, propellor, flight control board, LiPo battery, electronic speed controllers were used to perform the experimental set-up. An attempt has been made to design light weight drone compared to the conventional drones available. The drone is fabricated in such a manner that initially it performs downward motion into the well followed by the upward motion. All the components of a proposed drone have been fixed and checked for its working. The drone operates in a stable manner with four propellors and contributed its excellence for the underground application.

Orientation Determination in IMU Sensor with Complementary Filter

The use of unmanned aerial vehicles (UAV) systems has increased in recent years. Therefore,studies on UAVs have increased today. In this direction, the production of UAV systems with domestic resources has gained importance. In this study, it is desired to develop a domestic and national flight control card and software. In the flight control board designed for the UAV, it is aimed to keep the vehicle in balance in the air. Accurate measurement of platform orientation plays an important role in many applications such as aerospace, robotics, navigation, marine, machine interaction [1]. Inertial Measurement Unit (IMU) sensor was used to accurately measure the orientation of the UAV. IMU sensor is widely used in UAVs due to its light weight and low energy consumption. In this direction, the need for a filter has emerged in the IMU sensor, which is used to accurately measure the orientation of the unmanned aerial vehicle. In this study, a complementary filter was applied on the IMU sensor. Thanks to this filter, it has been observed that the accuracy of the data received from the IMU sensor has increased. Based on the data obtained, a Proportional Integral Derivative (PID) algorithm was developed, and the vehicle was kept in balance. In this study, ARMCortex-M4 based STM32F407VG microcontroller and MPU6050 as IMU sensor were used. Keil-uVision5 compiler is preferred for software. As a result, high accuracy in the orientation detection of unmanned aerial vehicles was obtained by applying a complementary filter on the IMU sensor.

Design and experimental study of a new flapping wing rotor micro aerial vehicle

A three-wing Flapping Wing Rotor Micro Aerial Vehicle (FWR-MAV) which can perform controlled flight is introduced and an experimental study on this vehicle is presented. A mechanically driven flapping rotary mechanism is designed to drive the three flapping wings and generate lift, and control mechanisms are designed to control the pose of the FWR-MAV. A flight control board for attitude control with robust onboard attitude estimation and a control algorithm is also developed to perform stable hovering flight and forward flight. A series of flight tests was conducted, with hovering flight and forward flight tests performed to optimize the control parameters and assess the performance of the FWR-MAV. The hovering flight test shows the ability of the FWR-MAV to counteract the moment generated by rotary motion and maintain the attitude of the FWR-MAV in space; the experiment of forward flight shows that the FWR-MAV can track the desired attitude.

Design, Manufacturing, and Flight Testing of an Experimental Flying Wing UAV

This paper presents the design, manufacturing, and flight testing of an electric-powered experimental flying wing unmanned aerial vehicle (UAV). The design process starts with defining the performance requirements including the stall speed, maximal speed, cruise altitude, absolute ceiling, and turn radius and speed. The wing loading and associated power loading are obtained based on the defined performance requirements. The wing area, UAV mass, and power requirements are determined from the endurance and payload requirements. The power requirement determines the motor size. Aerodynamics and stability designs are obtained based on the selected airfoil and obtained wing area. After completing the design, the UAV is manufactured using composite materials. The UAV is equipped with an AXi 4130/20 kv305 brushless motor and a Pixhawk flight control board. Its total weight is 8.6 kg. Flight tests were conducted to evaluate the UAV’s performance and dynamic characteristics and to demonstrate the success of the design.

KUBeetle-S: An insect-like, tailless, hover-capable robot that can fly with a low-torque control mechanism

For an insect-like tailless flying robot, flapping wings should be able to produce control force as well as flight force to keep the robot staying airborne. This capability requires an active control mechanism, which should be integrated with lightweight microcontrol actuators that can produce sufficient control torques to stabilize the robot due to its inherent instability. In this work, we propose a control mechanism integrated in a hover-capable, two-winged, flapping-wing, 16.4 g flying robot (KUBeetle-S) that can simultaneously change the wing stroke-plane and wing twist. Tilting the stroke plane causes changes in the direction of average thrust and the wing twist distribution to produce control torques for pitch and roll. For yaw (heading change), root spars of left and right wings are adjusted asymmetrically to change the wing twist during flapping motion, resulting in yaw torque generation. Changes in wing kinematics were validated by measuring wing kinematics using three synchronized high-speed cameras. We then performed a series of experiments using a six-axis force/torque load cell to evaluate the effectiveness of the control mechanism via torque generation. We prototyped the robot by integrating the control mechanism with sub-micro servos as control actuators and flight control board. Free flight tests were finally conducted to verify the possibility of attitude control.

Design of four axis aircraft based on Android control

A four axle aircraft is designed with the open source firmware MWC is used as the flight control board. The MPU6050 gyro sensor and BMP085 pressure sensor are used to acquire the attitude data of aircraft in real time. Combining the Calman filtering and mean filtering, the attitude data is filtered and fused to obtain more accurate attitude information. In the control algorithm, the PID control algorithm is adopted to control the speed of the motor, which ensures that the aircraft can quickly and stably change the attitude of the flight. The Android handset is connected to an aircraft by using the WiFi signal which is launched on the four axle aircraft. The user can control the aircraft by using the appropriate App. Experimental results show that: The four axle aircraft can realize the functions of attitude, heading and hover under the control of App, and the system has friendly interface, flexible operation, stable and reliable.

In-flight Re-Configurable Systems

Multirotors areproviding ease for various applications like, environmental monitoring, surveillance, spying, radiation data collection, indoor 3-D mapping and navigation etc. This paper introduces a design of multirotor which can reconfigure its size in-flight i.e. inflight re-configurable system (IRCS).The size can be changed by decreasing or increasing its arm length, using Rack and Pinion Type Mechanism (RPTM). In this a quadrotor has considered,it’s all four arm which have RPTM, are connected to a single high torque stepper motor which can control the length of arm based on vision decision. Camera connected to each arm will provide visual decision to reconfigure its shape and avoid collision or make accessible to constraint environment.The stability will be maintained by Adaptive PID Controllers (A-PID) and changes simultaneously based on its arm length. Feedback from stepper motor is linked to Autopilot Flight Control Board of System (AFCBS) which has ability to decide and give correct PID values to system to maintain level flight.

Platform and State Estimation Design of a Small-Scale UAV Helicopter System

This paper presents the development of a small-scale unmanned aerial vehicle (UAV) helicopter system based on a Raptor 90 hobby helicopter. Firstly, onboard avionics system and ground station are designed carefully. The onboard avionics system mainly consists of sensors, flight control board, RF modem, and power supply system. The ground station comprises a computer and a RF modem. The main function of ground station is to monitor the status of onboard avionics. To avoid the effect of noises, some efficient sensor data processing and integrated navigation algorithms are designed and implemented on the onboard avionics. As a result, the constructed system exhibits low weight, small size, antivibration, and low power consumption; the essential information for system identification and automatic control can be easily acquired. Several ground and flight tests have been performed to verify the feasibility and reliability of the total system. The results show that it is sufficient for system identification and automatic control.