• 대한임베디드공학회논문지
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• 제9권5호
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• pp.269-276
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• 2014

In recent, autonomous navigation techniques to avoid obstacles have been studied by using unmanned aircraft vehicles(UAVs) since the increment of UAV's interest and utilization. Particularly, autonomous navigation based UAVs are utilized in several areas such as military, police, media, and so on. However, there are still some problems to avoid obstacle when UVAs perform autonomous navigation. For instance, the UAV can not forward in the corner of corridors even though it utilizes the improved vanish point algorithm that makes an autonomous navigation system. Therefore, in this paper, we propose an obstacle avoidance technique based on immune algorithm for autonomous navigation of Quadrotor. The proposed algorithm is consisted of two steps such as 1) single color discrimination and 2) multiple color discrimination. According to the result of experiments, we can solve the previous problem of the improved vanish point algorithm and improve the performance of autonomous navigation of Quadrotor.

• 대한조선학회논문집
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• 제60권6호
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• pp.473-481
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• 2023

In this study, a simulation system was developed to verify autonomous navigation algorithm in complex maritime traffic areas. In particular, real-world maritime traffic scenario was applied by considering near real-time maritime traffic information provided by Korean e-Navigation service. For this, a navigation simulation system of Unmanned Surface Vehicle (USV) was integrated with an e-Navigation equipment, called Electronic Chart System (ECS). To verify autonomous navigation algorithm in the simulation system, initial conditions including initial position of an own ship and a set of paths for the ship to follow are assigned by an operator. Then, considering real-world maritime traffic information obtained from the service, the simulation is implemented in which the ship repeatedly travels by avoiding surrounding obstacles (e.g., approaching ships). In this paper, the developed simulation system and its application on verification of the autonomous navigation algorithm in complex maritime traffic areas are introduced.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권9호
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• pp.402-412
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• 2002

The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.134.6-134
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• 2001

The purpose of navigation algorithm is to reach a given target point without collision with obstacles while an autonomous mobile robot is navigating. To achieve a safe navigation, this paper presents an effective navigation algorithm for the autonomous mobile robot equipped with ultrasonic sensors in unknown environments. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The decision maker using fuzzy inference systems weights the steering angles selected ...

• 대한전기학회논문지:시스템및제어부문D
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• 제52권8호
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• pp.471-481
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• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• 한국산업융합학회 논문집
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• 제26권2_2호
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• pp.359-370
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• 2023

For a vehicle to follow a reference path accurately, its position must be estimated accurately and reliably. In this paper, we propose a lateral control algorithm for autonomous navigation of a vehicle via USAT(Ultrasonic Satellite System), which is an absolute position measurement system using an ultrasonic wave and INS(Inertial Navigation System) integration. In order to estimate the vehicle's parameters, a J-turn test is used. And the autonomous navigation performances of proposed lateral control algorithm and validity of proposed lateral control algorithm are verified and evaluated by simulation and experiments.

• 제어로봇시스템학회논문지
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• 제15권3호
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• pp.293-299
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• 2009

This paper discusses an autonomous navigation system for urban environments. For the localization of the robot, EKF (Extended Kalman Filter) algorithm is used with odometry, angle sensor, and DGPS (Differential Global Positioning System) measurement. Especially in an urban environment, DGPS is often blocked by buildings and trees and the resulting inaccurate positioning prevents the robot from safe and reliable navigation. In addition to the global information from DGPS, the local information of the curb on the roadway is used to track a route when the global DGPS information is inaccurate. For this purpose, curb detection algorithm is developed and implemented in the developed navigation algorithm. Four different types of navigation strategies are developed and they are switched to adapt to different localization conditions according to the availability of DGPS and the existence of the curbs on the roadway. The experimental results show that the designed switching strategy improves the navigation performance adapting to the environment conditions.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 춘계학술대회 논문집
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• pp.459-464
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• 2004

In this paper, an autonomous navigation system for autonomous guided vehicles (AGVs) operated in an automated container terminal is designed. The navigation system is based on the sensors detecting the range and bearing. The navigation algorithm used is an interacting multiple model (IMM) algorithm to detect other AGVs and avoid other obstacles using informations obtained from multiple sensors. As models to detect other AGVs (or obstacles), two kinematic models are derived： Constant velocity model for linear motion and constant speed turn model for curvilinear motion. For constant speed turn model, an unscented Kalman filter (UKF) is used because of drawbacks of the extended Kalman filter (EKF) in nonlinear system. The suggested algorithm reduces the root mean squares error for linear motions, while it can rapidly detect possible turning motions.

• 한국정밀공학회지
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• 제19권8호
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• pp.147-154
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• 2002

In this paper, a path navigation algorithm through use of a sensor platform is proposed. The sensor platform is composed of two electric motors which make panning and tilting motions. An algorithm for computing a real path and an obstacle length is developed by using a scanning method that controls rotation of the sensors on the platform. An Autonomous Robot Vehicle(ARV) can perceive the given path by adapting this algorithm. A sensor scanning method is applied to the sensor platform for using small numbers of sensor. The path navigation algorithm is composed of two parts. One is to perceive a path pattern, the other is used to avoid an obstacle. An optimal controller is designed for tracking the reference path which is generated by perceiving the path pattern. The ARV is operated using the optimal controller and the path navigation algorithm. Based on the results of actual experiments, this algorithm for an ARV proved sufficient for path navigation by small number of sensors and for a low cost controller by using the sensor platform with a scanning method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.