• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.617-624
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• 2010

This article describes the system architecture of KUVE (KIST Unmanned Vehicle Electric) and unmanned autonomous navigation of it in KIST. KUVE, which is an electric light-duty vehicle, is equipped with two laser range finders, a vision camera, a differential GPS system, an inertial measurement unit, odometers, and control computers for autonomous navigation. KUVE estimates and tracks the boundary of road such as curb and line using a laser range finder and a vision camera. It follows predetermined trajectory if there is no detectable boundary of road using the DGPS, IMU, and odometers. KUVE has over 80% of success rate of autonomous navigation in KIST.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.158-159
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• 2018

It analyzed the domestic and overseas trends related to smart ship development in the world and identifies key functions required for smart vessels, especially autonomous vessels, and introduces key technologies that can be utilized in the development of INS(Integrated Navigation System) for autonomous vessels.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.583-591
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• 2007

This paper describes the development of the $H_{\infty}$ lateral control system for an autonomous ground vehicle operating a limited area using the RTK-DGPS(Real Time Kinematic-Differential Global Positioning System). Before engaging in autonomous driving, map data are acquired by the RTK-DGPS and used to construct a reference trajectory. The navigation system contains the map data and computes the reference yaw angle of the vehicle using two consecutive position values. The yaw angle of the vehicle is controlled by the $H_{\infty}$ controller. A prototype of the autonomous vehicle by the navigation method has been developed, and the performance of the vehicle has been evaluated by experiment. The experimental results show that the $H_{\infty}$ controller and the RTK-DGPS based navigation system can sufficiently track the map at low speed. We expect that this navigation system can be made more accurate by incorporating additional sensors.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.429-434
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• 2005

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.81-81
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• 2018

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.251-257
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• 2012

Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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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.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.435-440
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• 2012

Recently autonomous navigation systems are taken great attention in real industry. The ability to performing desired tasks in rough, changing, unstructured and uncertain environments without continuous human assistance is needed in autonomous navigation systems including autonomous robots. Industrial Mobile robot can be required wireless network communications for the purpose of navigation information sharing. According to these backgrounds, in this paper, we develop sensor network and wireless network-based autonomous navigation systems, and provide experimental results in order to show the validity of the developed systems.