• 한국항행학회논문지
• /
• 제14권2호
• /
• pp.206-212
• /
• 2010

본 논문에서는 유비쿼터스 환경에서 로봇의 응용서비스를 제공하는데 필요한 네트워크로서 로보틱 지그비 네트워크의 개념을 소개하고 이를 이용한 응용 시나리오를 제시한다. 제시한 응용시나리오의 기본이 되는 네트워크 연결 및 데이터 전송에 관한 실험을 수행하였다. 이 실험 결과를 통해 앞으로 Robotic Zigbee Network를 이용한 위치인식 오차율을 최소화하는 로봇의 위치추정 및 추적 알고리즘 개발의 기반을 마련한다.

• 제어로봇시스템학회논문지
• /
• 제11권5호
• /
• pp.457-462
• /
• 2005

An empirical way of a covariance matrix which expresses the odometry uncertainty of mobile robots is proposed. This method utilizes PC-method which removes systematic errors of odometry. Once the systematic errors are removed, the odometry error can be modeled using the Gaussian probability distribution, and the parameters of the distribution can be represented by the covariance matrix. Experimental results show that the method yields $5{\%}$ and $2.3{\%}$ offset for the synchro and differential drive robots.

• 제어로봇시스템학회논문지
• /
• 제18권8호
• /
• pp.725-730
• /
• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• 전자공학회지
• /
• 제39권2호
• /
• pp.45-54
• /
• 2012

Object detection is a fundamental task for many high-level computer vision applications such as image retrieval, scene understanding, activity recognition, visual surveillance and many others. Although object detection is one of the most popular problems in computer vision and various algorithms have been proposed thus far, it is also notoriously difficult, mainly due to lack of proper models for object representation, that handle large variations of object structure and appearance. In this article, we review a branch of object detection algorithms based on Support Vector Machines (SVMs), a well-known max-margin technique to minimize classification error. We introduce a few variations of SVMs-Structural SVMs and Latent SVMs-and discuss their applications to object detection and localization.

• 로봇학회논문지
• /
• 제17권3호
• /
• pp.353-358
• /
• 2022

Due to the limited field of view of the pinhole camera, there is a lack of stability and accuracy in camera pose estimation applications such as visual SLAM. Nowadays, multiple-camera setups and large field of cameras are used to solve such issues. However, a multiple-camera system increases the computation complexity of the algorithm. Therefore, in multiple camera-assisted visual simultaneous localization and mapping (vSLAM) the multi-view tracking algorithm is proposed that can be used to balance the budget of the features in tracking and local mapping. The proposed algorithm is based on PanoSLAM architecture with a panoramic camera model. To avoid the scale issue 3D LiDAR is fused with omnidirectional camera setup. The depth is directly estimated from 3D LiDAR and the remaining features are triangulated from pose information. To validate the method, we collected a dataset from the outdoor environment and performed extensive experiments. The accuracy was measured by the absolute trajectory error which shows comparable robustness in various environments.

• 센서학회지
• /
• 제32권5호
• /
• pp.300-306
• /
• 2023

A hull-cleaning robot sticks to the surface of a vessel and moves for efficient cleaning. Precise path planning and tracking using the current position is crucial. Many robots rely on the INS algorithm, but errors accumulate. To fix this, GPS, sonar, and USBL are used, though with limitations. Selecting suitable sensors for the surface operation and accurate positioning algorithm are vital. In this study, we developed a robot position estimation algorithm using the structure of a ship. Problems that arise when expanding the 2D position estimation algorithm used in existing wall structures to 3D were evaluated and methods for solving them were proposed. In addition, we aimed to improve performance by deriving singularities that exist in the robot path and proposing an error correction algorithm based on the singularities.

• 한국군사과학기술학회지
• /
• 제21권4호
• /
• pp.447-455
• /
• 2018

If a hidden enemy is shooting, there is a threat against soldiers in recent conflicts. This paper aims to improve the localization of a muzzle using microphone array. Gunshot noise can provide information about the location of muzzle with two signals, the muzzle blast from the gun barrel and the projectile sound from the bullet. Two signals arrive to the microphone array with different arrival time and angle. If the arrival angles of the two signals are estimated, distance between sniper location and the microphone array can be calculated by using geometric principles. This method was established in 2003 by Pare. But this method has a limitation that it cannot calculate the distance when the arrival angles of the two signals are same. Also it has an error when the angle difference of arrival is small. In order to overcome this limitation, a new method is proposed that uses the change of characteristic of the projectile sound with respect to vertical distance from the trajectory. The proposed method estimates the distance correctly when the arrival angle of two signals are same, and when the angle difference between two signals is increased, the estimation error increases with respect to the angle. Therefore these two methods can be selected according to the angle difference between two signals to estimate the distance of the muzzle. Below the threshold of the angle difference, the proposed method can be used to estimate distance with smaller error than the existing method. This was demonstrated by shooting tests using actual sniper rifles.

• 제어로봇시스템학회논문지
• /
• 제16권12호
• /
• pp.1167-1175
• /
• 2010

This paper presents the use of the inertial measurement unit information and the infrared sector information for getting the position of an object. Travel distance is usually calculated from the double integration of the accelerometer output with respect to time; however, the accumulated errors due to the drift are inevitable. The orientation change of the accelerometer also causes error because the gravity is added to the measured acceleration. Unless three axis orientations are completely identified, the accelerometer alone does not provide correct acceleration for estimating the travel distance. We propose a way of minimizing the error due to the change of the orientation. In order to reduce the accumulated error, the infrared sector information is fused with the inertial measurement unit information. Infrared sector information has highly deterministic characteristics, different from RFID. By putting several infrared emitters on the ceiling, the floor is divided into many different sectors and each sector is set to have a unique identification. Infrared light based sector information tells the sector the object is in, but the size of the uncertainty is too large if only the sector information is used. This paper presents an algorithm which combines both the inertial measurement unit information and the sector information so that the size of the uncertainty becomes smaller. It also introduces a framework which can be used with other types of the artificial landmarks. The characteristics of the developed infrared light based sector and the proposed algorithm are verified from the experiments.

• 한국통신학회논문지
• /
• 제38C권2호
• /
• pp.141-154
• /
• 2013

신호수신장치들간 시각 동기화는 TDoA를 이용한 위치 탐지에 있어 가장 중요한 전제 사항이 된다. 본 논문에서는 시스템의 시각동기 정확도를 위하여 고정밀도의 OCXO와 DPLL을 이용하여 원자 클럭을 사용하는 GPS 위성으로부터 수신되는 1 pps(pulse per second) 신호에 위상동기 되는 방식을 제안한다. GPS 기반 고정밀 타이밍 레퍼런스의 성능은 근본적으로 매우 우수한 장기간에 걸친 주파수 안정도(long-term frequency stability)를 갖는 GPS 타이밍 신호의 특성을 따라간다고 볼 수 있으며, GPS 타이밍 신호에 동기가 되면 0.001 ppb(part per billion) 급의 초정밀 타이밍 레퍼런스를 통해 시각 동기의 정확도를 향상시킨다. 제안하는, 향상된 시각 동기 정확도를 통해 TDoA 기반의 위치 탐지 기술에서의 측정 오차를 평가하고, 시각동기 오차 개선 방법이 TDoA 기반의 위치 측정 오차를 크게 개선함을 보인다.

• 한국정보통신학회논문지
• /
• 제17권8호
• /
• pp.1926-1933
• /
• 2013

무선 센서 네트워크를 위한 다양한 위치 추적 알고리즘들이 제안되고 있다. IEEE 802.15.4a 기반의 위치인식 시스템은 두 노드간의 정밀한 거리측정 기능을 제공하며 이를 기반으로 정확도가 높은 위치 추정 서비스를 제공한다. 하지만 실내 환경에서는 다양한 장해물들로 인하여 Non-line-of-sight (NLOS) 경로가 발생한다. 이로 인하여 IEEE 802.15.4a 기반의 위치 인식 시스템에서는 위치 추정 시 추정된 위치 좌표의 정확도가 떨어지는 문제가 발생한다. 이를 해결하기 위하여 본 논문에서는 MST 토폴로지를 이용한 실내 환경에서의 위치측정에러를 보상하는 알고리즘을 제안한다. NanoPAN 5375 모트를 이용한 실내 환경에서의 실험 및 시뮬레이션 결과, 제안한 알고리즘은 기존에 제안된 위치 추정 알고리즘에 비하여 위치 정확도가 개선되었음을 확인하였다.