• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.2
• /
• pp.164-170
• /
• 2011

This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.766-771
• /
• 1992

The hydrodynamic coefficients estimation problem is important to develop an underwater vehicle and design a controller for it. In this paper, an identification theory, the Extended Kalman Filter, is applied to this parameter estimation problem. In the case that a process noise is not used, all of the parameters are almost exactly converged to the true values respectively. When a process noise is used, all of the parameters are converged to the true values, too, although some parameter estimates are slightly biased. The comparisons of the two trajectories between those generated by the true parameters and those by the estimated parameters show that the parameter estimation problem is well-solved.

• Journal of Mechanical Science and Technology
• /
• v.18 no.3
• /
• pp.370-378
• /
• 2004

An autonomous pipeline inspection gauge system has been developed for determining position, orientation, curvature, and deformations such as dents and wrinkles of operating pipelines by Korea Gas Company and Seoul National University. The most important part of several subsystems is the Strapdown Inertial Measurement Unit (SIMU), which is integrated with velocity and distance sensors, weld detection system, and digital recording device. The Geometry Pipeline Inspection Gauge (GeoPIG) is designed to operate continuously and autonomously for a week or longer in operating gas pipelines. In this paper, the design concepts, system integration, and data processing/analysis method for the PIG will be presented. Results from the recent experiment for a 58 kilometer gas pipeline will be discussed.

• Proceedings of the KIPE Conference
• /
• 2010.07a
• /
• pp.418-419
• /
• 2010

본 논문에서는 스크리닝에 기반한 리튬이온 배터리 팩의 state of charge (SOC) 추정방법을 연구하였다. 전기화학적 특성이 서로 유사한 셀들을 미리 선별하는 스크리닝 방법을 통해 직렬, 병렬, 직/병렬팩이 구성될 때, 이러한 팩의 전기화학적 등가회로 모델은 단위 셀 대비 일정한 경향성을 보이는 용량, open circuit voltage (OCV) 등의 파라미터 정보를 토대로 기존 단위 셀 모델과 동일한 모델 구축이 가능하다. 이를 통하여 extended kalman filter (EKF)를 이용한 배터리 팩의 SOC 추정이 가능함을 보인다.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.28-28
• /
• 2000

Low-cost solid-state inertial sensors of three rate Gyroscopes and a triaxial Accelerometer are evaluated in static and dynamic environments. As a interim result, error models of each inertial sensors are generated. Model parameters with respect to temperature are acquired in static environment. These error models are included in an Extended Kalman Filter(EKF) to compensate bias error due to temperature variation. Experimental results in dynamic environment are included to show the validity of the each error model and the performance improvement of a compensated low cost inertial sensors for a navigational application

• The Journal of Korea Robotics Society
• /
• v.3 no.1
• /
• pp.16-22
• /
• 2008

Recently, automatic parking assist systems are commercially available in some cars. In order to improve the reliability and the accuracy of parking control, pose uncertainty of a vehicle and some experimental issues should be solved. In this paper, following three schemes are proposed. (1) Odometry calibration scheme for the Car-Like Mobile Robot.(CLMR) (2) Accurate localization using Extended Kalman Filter(EKF) based redundant odometry fusion. (3) Trajectory tracking controller to compensate the tracking error of the CLMR. The proposed schemes are experimentally verified using a miniature Car-Like Mobile Robot. This paper shows that odometry accuracy and trajectory tracking performance can be dramatically improved by using the proposed schemes.

• The Journal of Korea Robotics Society
• /
• v.11 no.4
• /
• pp.226-234
• /
• 2016

In this study, a model-referenced underwater navigation algorithm is proposed for high-precise underwater navigation using monocular vision near underwater structures. The main idea of this navigation algorithm is that a 3D model-based pose estimation is combined with the inertial navigation using an extended Kalman filter (EKF). The spatial information obtained from the navigation algorithm is utilized for enabling the underwater robot to navigate near underwater structures whose geometric models are known a priori. For investigating the performance of the proposed approach the model-referenced navigation algorithm was applied to an underwater robot and a set of experiments was carried out in a water tank.

• Proceedings of the KIPE Conference
• /
• 2018.07a
• /
• pp.240-242
• /
• 2018

본 논문은 배터리 등가 회로 모델의 파라미터를 실시간으로 추정 가능한 온라인 업데이트 알고리즘을 비교 분석한다. 온라인 업데이트 알고리즘은 EKF (Extended Kalman Filter)와 RLS (Recursive Least Square)를 기반으로 구성되며 Li-ion 배터리를 이용한 실험 결과를 통하여 각 알고리즘의 연산량, 정확도 등을 분석한다. 분석된 결과를 바탕으로 적용 시스템의 환경과 특성에 따라 적합한 온라인 업데이트 알고리즘을 제안한다.

• Proceedings of the KIPE Conference
• /
• 2018.07a
• /
• pp.249-251
• /
• 2018

본 논문에서는 모델 기반 적응제어 방식중 하나인 확장 칼만 필터(EKF: Extended Kalman Filter)를 사용하여 전기자전거용 배터리팩의 충전량(SOC: State of Charge)을 상온과 저온에서 추정하였다. 온도에 따라 배터리의 특성은 매우 가변적이며, 모델의 특성이 달라짐에 따라 적응제어를 위한 내부 파라미터 또한 상이하게 나타난다. 본 논문에서는 Matlab/Simulink를 이용하여 배터리와 확장 칼만 필터를 설계하고 시뮬레이션하였다. 온도에 따른 최적의 SOC 추정 성능을 얻기 위해, 오차 원인을 분석하고 이에 따른 개선된 SOC 추정 결과를 나타냈다.

• The Journal of Korea Robotics Society
• /
• v.6 no.3
• /
• pp.292-300
• /
• 2011

Global positioning system (GPS) is widely used to measure the position of a vehicle. However, the accuracy of the GPS can be severely affected by surrounding environmental conditions. To deal with this problem, the GPS and odometry data can be combined using an extended Kalman filter. For stable navigation of an outdoor mobile robot using the GPS, this paper proposes two methods to evaluate the reliability of the GPS data. The first method is to calculate the standard deviation of the GPS data and reflect it to deal with the uncertainty of the GPS data. The second method is to match the GPS data to the traversability map which can be obtained by classifying outdoor terrain data. By matching of the GPS data with the traversability map, we can determine whether to use the GPS data or not. The experimental results show that the proposed methods can enhance the performance of the GPS-based outdoor localization.