• 한국군사과학기술학회지
• /
• 제19권1호
• /
• pp.9-15
• /
• 2016

Source localization has developed in various fields of signal processing including radar, sonar, and wireless communication, etc. Source localization can be found by estimating the time difference of arrival between the each of sensors. Several methods like the NLS(Nonlinear Least Square) cost function have been proposed in order to improve the performance of time delay estimation. In this paper, we propose a clustering method using the four sensors with the same aperture as previous methods of using the three sensors. Clustering method can be improved the source localization performance by grouping similar estimated values. The performance of source localization using clustering method is evaluated by Monte Carlo simulation.

• 로봇학회논문지
• /
• 제9권3호
• /
• pp.154-159
• /
• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• 터널과지하공간
• /
• 제32권3호
• /
• pp.231-242
• /
• 2022

본 연구에서는 지하광산에서 로봇의 위치를 추정하고, 여러 경유지를 거쳐 주행한 후 원위치로 복귀하는 ROS (Robot Operating System) 기반의 자율주행 로봇을 개발하였다. 자율주행 로봇은 SLAM (Simultaneous Localization And Mapping) 기술을 활용하여 주행 경로에 대한 전역 지도를 사전에 생성한다. 이후, 라이다 센서를 통해 측정되는 벽면의 형태와 전역 지도를 매칭하고 AMCL (Adaptive Monte Carlo Localization) 기법을 통해 데이터들을 융합하여 로봇의 위치를 보정한다. 또한, 라이다 센서를 통해 전방 주행환경을 인지하고, 장애물을 회피한다. 개발된 자율주행 로봇을 활용하여 지하광산 현장을 모사한 실내 실험장을 대상으로 주행 실험을 수행하였다. 그 결과, 자율주행 로봇은 다중 지점의 경유지에 대해 순차적으로 주행하고 장애물을 회피하며 안정적으로 복귀하는 것을 확인할 수 있었다.

• 한국전기화학회:학술대회논문집
• /
• 한국전기화학회 2004년도 수소연료전지공동심포지움 2004논문집
• /
• pp.287-292
• /
• 2004

In order to understand the relationship between molecular structure of Metal-Organic Framework(MOF) and capacity of hydrogen absorption, quantum mechanical calculations and grand canonical Monte Carlo simulations have been carried out on a series of MOF-5 having various organic linkers. The calculation results about specific surface area and electron density for various frameworks indicated that the capacity of the hydrogen storage is largely dependent on effective surface area rather than the free volume. Based on the iso-electrostatic potential surface from density functional calculation and the amount of adsorbed hydrogens from grand canonical Monte Carlo calculation, it was also found that the electron localization ground organic linker plays an important role in hydrogen capacity of MOFs.

• 로봇학회논문지
• /
• 제9권1호
• /
• pp.28-38
• /
• 2014

This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn't yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

• ETRI Journal
• /
• 제37권3호
• /
• pp.533-540
• /
• 2015

In wireless localization, several linear closed-form solution (LCS) methods have been investigated as a direct result of the drawbacks that plague the existing iterative methods, such as the local minimum problem and heavy computational burden. Among the known LCS methods, both the direct solution method and the difference of squared range measurements method are considered in this paper. These LCS methods do not have any of the aforementioned problems that occur in the existing iterative methods. However, each LCS method does have its own individual error property. In this paper, a hybrid LCS method is presented to reduce these errors. The hybrid LCS method integrates the two aforementioned LCS methods by using two check points that give important information on the probability of occurrence of each LCS's individual error. The results of several Monte Carlo simulations show that the proposed method has a good performance. The solutions provided by the proposed method are accurate and reliable. The solutions do not have serious errors such as those that occur in the conventional standalone LCS and iterative methods.

• 제어로봇시스템학회논문지
• /
• 제19권7호
• /
• pp.633-639
• /
• 2013

Several estimation methods used in the range measurement based wireless localization area have individual problems. These problems may not occur according to certain application areas. However, these problems may give rise to serious problems in particular applications. In this paper, three methods, ILS (Iterative Least Squares), DS (Direct Solution), and DSRM (Difference of Squared Range Measurements) methods are considered. Problems that can occur in these methods are defined and a simple hybrid solution is presented to solve them. The ILS method is the most frequently used method in wireless localization and has local minimum problems and a large computational burden compared with closed-form solutions. The DS method requires less processing time than the ILS method. However, a solution for this method may include a complex number caused by the relations between the location of reference nodes and range measurement errors. In the near-field region of the complex solution, large estimation errors occur. In the DSRM method, large measurement errors occur when the mobile node is far from the reference nodes due to the combination of range measurement error and range data. This creates the problem of large localization errors. In this paper, these problems are defined and a hybrid localization method is presented to avoid them by integrating the DS and DSRM methods. The defined problems are confirmed and the performance of the presented method is verified by a Monte-Carlo simulation.

• 한국전자통신학회논문지
• /
• 제6권1호
• /
• pp.148-156
• /
• 2011

본 논문은 실내 이동로봇의 자율주행 방법을 적용한 결과를 기술한다. 구체적으로 지도생성, 위치추정, 장애물 회피, 경로계획에 대해서 설명한다. 기하학적 지도는 위치추정과 경로계획에 이용된다. 위치 추정을 위해서 지도 정보를 이용하여 센서 데이터를 계산하고 이를 실제 센서 데이터와 비교한다. 위치 추정에는 몬테 카를로 위치 추정 방법을 사용한다. 인공 전위계를 사용하여 장애물로부터의 척력과 목표 위치로의 인력을 구하여 장물을 피한다. 경로계획을 위해 다익스트라 알고리즘을 이용하여 로봇의 출발 위치에서 목표 위치까지의 최단거리 경로를 구한다. 이러한 방법들이 통합하여 자율 주행 방법을 실제로 구현하여 실험하였다. 실제 실험을 통하여 제안한 방법이 로봇을 안전하게 자율주행하게 함을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권2호
• /
• pp.703-722
• /
• 2016

Passive wireless devices have increasing civilian and military applications, especially in the scenario with wearable devices and Internet of Things. In this paper, we study indoor localization of a target equipped with radio-frequency identification (RFID) device in ultra-wideband (UWB) wireless networks. With known room layout, deterministic multipath components, including the line-of-sight (LOS) signal and the reflected signals via multipath propagation, are employed to locate the target with one transmitter and a single inaccurate receiver. A factor graph corresponding to the joint posterior position distribution of target and receiver is constructed. However, due to the mixed distribution in the factor node of likelihood function, the expressions of messages are intractable by directly applying belief propagation on factor graph. To this end, we approximate the messages by Gaussian distribution via minimizing the Kullback-Leibler divergence (KLD) between them. Accordingly, a parametric message passing algorithm for indoor passive localization is derived, in which only the means and variances of Gaussian distributions have to be updated. Performance of the proposed algorithm and the impact of critical parameters are evaluated by Monte Carlo simulations, which demonstrate the superior performance in localization accuracy and the robustness to the statistics of multipath channels.

• 한국통신학회논문지
• /
• 제41권9호
• /
• pp.1060-1068
• /
• 2016

연결정보만을 이용하는 range-free 측위 기법의 성능은 이동성을 갖는 무선 단말 움직임에 취약한 문제점이 있다. 본 논문은 실제 전파 환경을 고려한 실내 네트워크에서 베이지안 필터를 사용하여 실시간으로 움직이는 무선장치를 추적하는 두 가지 알고리즘을 제안하였다. 제안하는 알고리즘은 측정 모델의 선형성에 따라 Kalman filter 와 Markov Chain Monte Carlo (MCMC) particle filter를 적용하였다. Kalman과 MCMC particle filter 기반 알고리즘은 각각 무선단말 간 연결정보를, 이동 단말의 한 홉 간격 내 단말로부터 수신하는 신호의 세기 (RSS: received signal strength)와 연결정보를 혼합한 융합정보를 측정 모델로 사용하였다. 정확한 시뮬레이션을 위해 실내 쇼핑몰 지도를 구현한 네트워크 지형, 그리고 라디오 불규칙도 모델을 적용하였다. 또한, 장애물 존재 여부에 따라 라디오 불규칙도를 분류하였다. 성능평가를 위해 MATLAB 시뮬레이션을 수행하였으며, 기존 range-free 측위 기법보다 향상된 위치정확도를 확인하였다.