• 대한전자공학회논문지TE
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• 제42권4호
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• pp.33-40
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• 2005

본 논문에서는 이동 로봇 주위의 환경 인식과 자기 위치 인식을 위하여 초음파 센서와 한 개의 카메라를 이용하여 안정적인 이동 경로를 확보할 수 있는 방식을 제시하였다. 개발된 초음파 센서(SRF04)시스템은 주행환경의 지도 작성을 위하여 목표물의 특징 데이터를 작성하고, SDC313(SAMSUNG) 카메라에서 수집된 영상자료와 결합하도록 하여 안정적인 경로탐색이 가능한 이동로봇 제어방식을 실험을 통하여 구현하였다.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.485-493
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• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• Journal of Construction Engineering and Project Management
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• 제6권2호
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• pp.30-39
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• 2016

This research presents the development of a self-governing mobile robot navigation system for indoor construction applications. This self-governing robot navigation system integrated robot control units, various positioning techniques including a dead-reckoning system, a UWB platform and motion sensors, with a BIM path planner solution. Various algorithms and error correction methods have been tested for all the employed sensors and other components to improve the positioning and navigation capability of the system. The research demonstrated that the path planner utilizing a BIM model as a navigation site map could effectively extract an efficient path for the robot, and could be executed in a real-time application for construction environments. Several navigation strategies with a mobile robot were tested with various combinations of localization sensors including wheel encoders, sonar/infrared/thermal proximity sensors, motion sensors, a digital compass, and UWB. The system successfully demonstrated the ability to plan an efficient path for robot's movement and properly navigate through the planned path to reach the specified destination in a complex indoor construction site. The findings can be adopted to several potential construction or manufacturing applications such as robotic material delivery, inspection, and onsite security.

• 로봇학회논문지
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• 제9권2호
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• 로봇학회논문지
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• 제3권1호
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.85-86
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• 2011

• 전자공학회논문지SC
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• 제42권2호
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• pp.1-10
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• 2005

본 논문에서는 이동로봇에 장착된 단일 초음파 센서 회전 모듈을 이용하여 구조화가 잘 된 실내 환경에 대한 지도를 작성하고 작성된 지도를 바탕으로 로봇의 자기 위치를 보정하는 데 있어서 지도작성과 위치 보정에 대한 정량화를 통해 성능을 향상시키기 위한 방법을 제시한다 이동로봇의 환경은 물체의 형상, 즉 직선, 모서리 ,곡선 등의 기하학적인 형상으로 표현되는 지도를 구성하고 초음파센서의 거리정보로부터 동일거리영역(Region of Constant Depth: RCD)을 분류하였다. 그리고 물리적 기반의 초음파 센서모델을 적용하여 주행중인 이동로봇의 자기위치 추정할 수 있도록 확장 칼만필터를 이용하였다 제시된 방법을 이용하여 시뮬레이션을 통하여 제시한 방법을 검증하고 실내 환경에서의 실험을 통해서 그 성능을 제시하고 있다.

• 제어로봇시스템학회논문지
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• 제11권12호
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• pp.1068-1076
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• 2005

In order to increase the autonomous navigation capability of a mobile robot, it is very crucial to develop a method for the robot to be able to recognize a priori hon structured environmental characteristics. This paper proposes an ultrasonic sensor based real-time method for recognizing a priori known structured indoor environmental characteristics like a wall and comer Unlike the methods reported in the literature the information obtained from the sensor can be processed in real-time by extended Kalman filter to update estimations of the position and orientation of robot with respect to known environmental characteristics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1844-1845
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• 2011

In this paper, we compared several localization methods for indoor mobile robot navigation using a global ultrasonic sensor network. To estimate the pose of mobile robot in the sensor network, the range or range difference information with or without robot kinematics is used. Simulation results showed that the localization methods with robot kinematics have better performances.

• 제어로봇시스템학회논문지
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• 제15권2호
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• pp.218-224
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• 2009

This paper proposes an effective SLAM based on redundant extended Kalman filter for robot navigation in an irregular surface to enhance the accuracy of robot's pose. To establish an accurate model of a caterpillar type robot is very difficult due to the mechanical complexity of the system which results in highly nonlinear behavior. In addition, for robot navigation on an irregular surface, its control suffers from the uncertain pose of the robot heading closely related to the condition of the floor. We show how this problem can be overcome by the proposed approach based on redundant extended Kalman filter through some computer simulation results.