• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1227-1230
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• 2003

In this paper, we propose a pose estimation method using local map acquired from 2d laser range finder information. The proposed method uses extended kalman filter. The state equation is a navigation system equation of Nomad Super Scout II. The measurement equation is a map-based measurement equation using a SICK PLS 101-112 sensor. We describe a map consisting of geometric features such as plane, edge and corner. For pose estimation we scan external environments by laser rage finer. And then these data are fed to kalman filter to estimate robot pose and position. The proposed method enables very fast simultaneous map building and pose estimation.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.99-105
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• 2008

To achieve autonomous mobile robot navigation, accurate localization technique is the fundamental issue that should be addressed. In augmented reality, the position of a user is required for location-based services. This paper presents indoor localization using infrared reflective artificial landmarks. In order to minimize the disturbance to the user and to provide the ease of installation, the passive landmarks are used. The landmarks are made of coated film which reflects the infrared light efficiently. Infrared light is not visible, but the camera can capture the reflected infrared light. Once the artificial landmark is identified, the camera's relative position/orientation is estimated with respect to the landmark. In order to reduce the number of the required artificial landmarks for a given environment, the pan/tilt mechanism is developed together with the distortion correction algorithm.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.389-395
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• 2022

In order to ensure reliability the high-level automated driving such as Advanced Driver Assistance System (ADAS) and universal robot taxi provided by autonomous driving systems, the operation with high integrity must be generated within the defined Operation Design Domain (ODD). For this, the position and posture accuracy requirements of autonomous driving systems based on the safety driving requirements for autonomous vehicles and domestic road geometry standard are necessarily demanded. This paper presents localization requirements for safe road driving of autonomous ground vehicles based on the requirements of the positioning system installed on autonomous vehicle systems, the domestic road geometry standard and the dimensions of the vehicle to be designed. Based on this, 4 Protection Levels (PLs) such as longitudinal, lateral, vertical PLs, and attitude PL are calculated. The calculated results reveal that the PLs are more strict to urban roads than highways. The defined requirements can be used as a basis for guaranteeing the minimum reliability of the designed autonomous driving system on roads.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.846-851
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• 2004

In this paper, we propose a global ultrasonic system for the self-localization and autonomous navigation of indoor mobile robots. The ultrasonic sensor is regarded as the most cost-effective ranging system among the possible alternatives, and it is widely used for general purpose, since it requires simple electronic drivers and has relatively high accuracy. The global ultrasonic system presented in this paper consists of four or more ultrasonic generators fixed at reference positions in the global coordinates of an indoor environment and two receivers mounted on the mobile robots. By using the RF (Radio Frequency) modules added to the ultrasonic sensors, the robot is able to control the ultrasonic generation and to obtain the critical distances from the reference positions, which are required in order to localize is position in the global coordinates. A kalman filter algorithm designed for the self-localization using the global ultrasonic system and the experimental results of the autonomous navigation are presented in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.37-40
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• 2007

Digital Magnetic Compass(DMC)는 실내의 전자기적 요소나 강한 자성체 건물구조에서는 쉽게 방해를 받던 Compass보다 실내에서 간섭에 강한 특징을 가지고 있다. 그리고 적외선 센서와 초음파 센서는 서로 물체와의 거리를 보완적으로 계산해 줄뿐만 아니라 값싼 센서로서 경제적인 이점을 가지고 있어 Simultaneous Localization and Mapping(SLAM)에서 많이 사용하고 있다. 본 논문에서는 자율 이동 로봇의 구동에서 Digital Magnetic Compass(DMC)와 Ultrasonic Sensors을 이용한 SLAM의 구현에 대해 연구하였다. 로봇의 특성상 한정된 Sensing 데이터만으로 방향과 위치를 파악하고 그 데이터 값으로 가능한 빠르게 Localization을 하여야 한다. 그러므로 자율 이동 로봇에서의 SLAM 적용함으로 Localization 구현과 Mapping을 수행하고 SLAM 구현상의 주된 연구 중의 하나인 Kid Napping 문제에 중점을 두고 연구한다. 특히, Localization 구현을 수행을 위한 데이터의 Sensing 방법으로 적외선 센서와 초음파 센서를 같이 사용하였고 비슷한 위치의 데이터 값이 주어지거나 사전 정보 없는 상태에서는 로봇의 상태를 파악하기 위해서 DMC을 같이 사용하여 더 정확한 위치를 측정에 활용하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.34.5-34
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• 2002

In this paper we propose a new method for modeling indoor environment with stereo camera and suggest a localization method for mobile robot navigation on the basis of it. From the viewpoint of easiness in map building and exclusion of artificiality, the main idea of this paper is that environment is represented as global topological map and each node has omni-directional metric and color information by using stereo camera and pan/tilt mechanism. We use the depth and color information itself in image pixel as feature for environmental abstraction. In addition, we use only the depth and color information at horizontal centerline in image, where optical axis is passing. The usefulness of this m...

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.55-57
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• 2018

In Simultaneous Localization and Mapping (SLAM), the robot acquire its map of environment while simultaneously localize itself relative to the map. Now a day, a map acquired by the mobile robots limit to specific area, in an indoor environment and cannot able to navigate autonomous between different floors. We propose a design that could able to overcome this issue in order to navigate multiple floors with one end goal mission to a target destination in the course of autonomous navigation. In this research, we consider all the floors have identical structural arrangement. Internet of Things (IoT) playing crucial role in bridging between "things" and Robot Operating System (ROS) enabled mobile robots.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.805-812
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• 2013

This paper describes the design, control, and localization which comprise major aspects of the development of underwater robots for the mine disposal. The developed robots are called the Mine Killer (MK-1) and MK-2. MK-1 had been developed from September 2009 and was presented at the 9-th International Symposium at NPS Monterey CA, on May 17-21, 2010[1]. The paper presents design of MK-1 and MK-2 in detail with comparison of these two versions of MKs. Then it derives hydrodynamic coefficients of MK-1. Based on the coefficients, the motion of MK-1 is simulated for straight line motion and circular motion. Also simulation results for PD control, LQ control and sliding mode control are presented. Finally, it shows a particle filter method for localization of MK-1 and MK-2 using simple range data from acoustic beacons.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.197-209
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• 2011

This paper presents a localization system using ceiling images in a large indoor environment. For a system with low cost and complexity, we propose a single camera based system that utilizes ceiling images acquired from a camera installed to point upwards. For reliable operation, we propose a method using hybrid features which include natural landmarks in a natural scene and artificial landmarks observable in an infrared ray domain. Compared with previous works utilizing only infrared based features, our method reduces the required number of artificial features as we exploit both natural and artificial features. In addition, compared with previous works using only natural scene, our method has an advantage in the convergence speed and robustness as an observation of an artificial feature provides a crucial clue for robot pose estimation. In an experiment with challenging situations in a real environment, our method was performed impressively in terms of the robustness and accuracy. To our knowledge, our method is the first ceiling vision based localization method using features from both visible and infrared rays domains. Our system can be easily utilized with a variety of service robot applications in a large indoor environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.99-107
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• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).