• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.122-130
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• 2012

Airborne separation assurance is a key requirement for Free Flight. This paper is to propose autonomous flight algorithm, such as extended authority of delegation, efficiency of airspace issue to deal with the empirical solution for free flight, and to measure flight efficiency and conflict detection and resolution (CD&R) by utilizing flight performance data under the two circumstances of scenario with the modeling of proposed algorithm and potential field algorithm. The results show that the autonomous flight algorithm is superior to the potential field algorithm under the circumstances of free flight airspace in terms of algorithm performance, CD&R, and flight efficiency.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.193-200
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• 2016

This paper introduces an algorithm to middle-low price drone's autonomous navigation flight system using computer vision and GPS. Existing drone operative system mainly contains using methods such as, by inputting course of the path to the installed software of the particular drone in advance of the flight or following the signal that is transmitted from the controller. However, this paper introduces new algorithm that allows autonomous navigation flight system to locate specific place, specific shape of the place and specific space in an area that the user wishes to discover. Technology developed for military industry purpose was implemented on a lower-quality hobby drones without changing its hardware, and used this paper's algorithm to maximize the performance. Camera mounted on middle-low price drone will process the image which meets user's needs will look through and search for specific area of interest when the user inputs certain image of places it wishes to find. By using this algorithm, middle-low price drone's autonomous navigation flight system expect to be apply to a variety of industries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.595-609
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• 2020

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.97-107
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• 2011

This paper describes efficient flight control algorithms for building a reconfigurable ad-hoc wireless sensor networks between nodes on the ground and airborne nodes mounted on autonomous vehicles to increase the operational range of an aerial robot or the communication connectivity. Two autonomous flight control algorithms based on adaptive gradient climbing approach are developed to steer the aerial vehicles to reach optimal locations for the maximum communication throughputs in the airborne sensor networks. The first autonomous vehicle control algorithm is presented for seeking the source of a scalar signal by directly using the extremum-seeking based forward surge control approach with no position information of the aerial vehicle. The second flight control algorithm is developed with the angular rate command by integrating an adaptive gradient climbing technique which uses an on-line gradient estimator to identify the derivative of a performance cost function. They incorporate the network performance into the feedback path to mitigate interference and noise. A communication propagation model is used to predict the link quality of the communication connectivity between distributed nodes. Simulation study is conducted to evaluate the effectiveness of the proposed reconfigurable airborne wireless networking control algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.323-328
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• 2011

In real system application, the 3-D obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: the sonar offers the range/bearing information of obstacles in a local detection area, it requires the system that has reduced acoustic noise and power consumption in terms of the autonomous underwater vehicle (AUV), it has the UFV operation constraints such as maximum pitch and depth, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent 3-D obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the 3-D obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.207-213
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• 2005

This paper deals with an autonomous flight guidance and control algorithm design for TR301 tilt-rotor airplane under development by Korea Aerospace Research Institute for simulation purpose. The objective of this study is to design autonomous flight algorithm in which the tilt-rotor airplane should follow the given waypoints precisely. The approach to this objective in this study is that, first of all, model-based inversion is applied to the highly nonlinear tilt-rotor dynamics, where the tilt-rotor airplane is assumed to fly at helicopter flight mode(nacelle angle=0 deg), and then the control algorithm, based on classical control, is designed to satisfy overall system stabilization and precise waypoint following performance. Especially, model uncertainties due to the tiltrotor model itself and inversion process are adaptively compensated in a simple neural network(Sigma-Phi NN) for performance robustness. The designed algorithm is evaluated in the tilt-rotor nonlinear airplane in helicopter flight mode to analyze the following performance for given waypoints. The simulation results show that the waypoint following responses for this algorithm are satisfactory, and control input responses are within control limits without saturation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.635-640
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• 2009

In real system application, the obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: it has local information because the sonar can only offer the obstacle information in a local detection area, it requires a continuous control input because the system that has reduced acoustic noise and power consumption is necessary, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.2
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• pp.109-117
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• 2018

The experimental results are presented of an autonomous flight algorithm of a foldable quadcopter with airdrop launching functions. A foldable wing structure enabled the quadcopter to be inserted into a rocket container with limited space. The foldable quadcopter was then separated from the rocket in the air. The flight pattern was tracked using a global positioning system (GPS) with various sensors, including an inertial measurement unit (IMU) module until a designated target position was reached. Extensive field tests were conducted through an international rocket competition, ARLISS 2017, which was held in Black Rock Desert, Nevada, USA. The flight trajectory record of the experiments is stored in electrically erasable programmable read-only memory (EEPROM) embedded in the main control unit. The flight record confirmed that the quadcopter successfully separated from the rocket, executed flight toward the target for a certain length of time, and stably landed on the ground.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.6
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• pp.458-464
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• 2013

This paper presents an algorithm for autonomous landing approach of a unmanned aerial vehicle. The main purpose of the autonomous landing approach in this study is to help a safe landing at night. From any initial position of the aircraft when this function is engaged, a flight path command is generated from the initial position. The shortest combination of an initial circular arc, a straight line segment, and a final circular arc is chosen for the flight path that will lead the aircraft to one end of runway for a landing. The algorithm is initially validated through numerous simulations with various initial conditions of aircraft. Then it is successfully validated through a number of flight tests.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.121-127
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• 2011

This paper presents an autonomous formation flight algorithm for micro aerial vehicles (MAVs) and its flight test results. Since MAVs have severe limits on the payload and flight time, formation of MAVs can help alleviate the mission load of each MAV by sharing the tasks or coverage areas. The proposed formation guidance law is designed using nonlinear dynamic inversion method based on 'Leader-Follower' formation geometric relationship. The sensing of other vehicles in a formation is achieved by sharing the vehicles' states using a high-speed radio data link. the designed formation law was simulated with flight data of MAV to verify its robustness against sensor noises. A series of test flights were performed to validate the proposed formation guidance law. The test result shows that the proposed formation flight algorithm with inter-communication is feasible and yields satisfactory results.