• 전자공학회논문지SC
• /
• 제47권1호
• /
• pp.67-75
• /
• 2010

본 논문에서는 실외환경에서 주행하는 이동로봇의 위치를 추정하는 알고리즘을 제안한다. 실외환경은 실내와 다르게 바닥이 고르지 않고, 경사진 지형 등 지면에 대한 불확실성을 포함한다. 이러한 환경에서 로봇의 진행 방향을 추정하기 위해 magnetic 센서 또는 IMU(Inertial Measurement Unit)가 예전부터 많이 사용되어 왔다. Magnetic 센서는 진행방향에 대한 절대 각도를 알려주며, IMU는 센서 내부에서 자이로스코프와 가속도계, 전자 나침반을 사용하여 각도 정보를 제공한다. 하지만 본 연구에 사용된 이동로봇은 전기자동차로써 자기장의 영향을 많이 받기 때문에 위 두 센서를 사용할 수가 없는 실정이다. 그래서 자기장의 영향을 받지 않는 1축 자이로 센서 3개를 이용한 자이로 모듈을 구성하여 진행방향을 추정하는 알고리즘을 구현하였다. GPS와 엔코더, 자이로 센서 모듈 등을 통해 얻은 정보를 융합하여 확장 칼만 필터 알고리즘에 의한 이동로봇의 위치추정 알고리즘을 개발하였고 실험을 통하여 제안한 알고리즘의 성능을 검증하였다.

• 제어로봇시스템학회논문지
• /
• 제10권1호
• /
• pp.81-86
• /
• 2004

This paper describes self-localization of a mobile robot from the multiple candidates of landmarks in outdoor environment. Our robot uses omnidirectional vision system for efficient self-localization. This vision system acquires the visible information of all direction views. The robot uses feature of landmarks whose size is bigger than that of others in image such as building, sculptures, placard etc. Robot uses vertical edges and those merged regions as the feature. In our previous work, we found the problem that landmark matching is difficult when selected candidates of landmarks belonging to region of repeating the vertical edges in image. To overcome these problems, robot uses the merged region of vertical edges. If interval of vertical edges is short then robot bundles them regarding as the same region. Thus, these features are selected as candidates of landmarks. Therefore, the extracted merged region of vertical edge reduces the ambiguity of landmark matching. Robot compares with the candidates of landmark between previous and current image. Then, robot is able to find the same landmark between image sequences using the proposed feature and method. We achieved the efficient self-localization result using robust landmark matching method through the experiments implemented in our campus.

• 제어로봇시스템학회논문지
• /
• 제15권8호
• /
• pp.845-850
• /
• 2009

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

• 센서학회지
• /
• 제17권1호
• /
• pp.53-60
• /
• 2008

Localization is the most important functions in mobile robots. There are so many approaches to realize this essential function in wheel based mobile robots, but it is not easy to find similar examples in small underwater robots. It is presented the sonar localization system using ubiquitous sensor network for a fish robot in this paper. A fish robot uses GPS and sonar system to find exact localization. Although GPS is essential tool to obtain positional information, this device doesn't provide reasonable resolution in localization. To obtain more precise localization information, we use several Ubiquitous Sensor Networks (USN) motes with sonar system. Experimental results show that a fish robot obtains more detailed positional information.

• 제어로봇시스템학회논문지
• /
• 제18권6호
• /
• pp.594-600
• /
• 2012

Accurate localization is very important to stable navigation of a mobile robot. This paper deals with local localization of a mobile robot especially for outdoor environments. The GPS information is the easiest way to obtain the outdoor position information. However, the GPS accuracy can be severely affected by environmental conditions. To deal with this problem, the GPS and wheel odometry can be combined using an EKF (Extended Kalman Filter). However, this is not enough for safe navigation of a mobile robot in outdoor environments. This paper proposes a novel method using lane features from the road image. The pose data of a mobile robot can be corrected by analyzing the detected lane features. This can improve the accuracy of the localization process substantially.

• 한국지능시스템학회논문지
• /
• 제15권5호
• /
• pp.560-566
• /
• 2005

본 논문은 유비쿼터스 이동로봇의 자기위치인식에 적용되는 비젼시스템의 왜곡된 영상을 보정하기 위한 실용적인 방법을 제안하다. 이동로봇에서 자기위치인식은 필수적인 요소이며 카메라 비젼시스템을 이용하여 처리 가능하다. 자기위치인식에서 비젼시스템은 넓은 시야를 확보하기 위해 어안렌즈를 이용하는데, 이는 영상의 왜곡을 발생한다. 또한 이동로봇은 지속적인 움직임을 가지므로 빠른 시간 내에 영상을 처리하여 자기위치를 인식해야 한다. 따라서 이동로봇에 적용 가능한 실용적인 영상왜곡 보정기법을 제안하고 실험을 통하여 성능을 검증한다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1456-1459
• /
• 2005

To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data. The effectiveness of the proposed localization scheme is demonstrated by the experiments.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
• /
• pp.103-105
• /
• 2009

This paper presents a pseudorandom tag arrangement for improved RFID based mobile robot localization. First, four repetitive tag arrangements, including square, parallelogram, tilted square, and equilateral triangle, are examined. For each tag arrangement, the difficulty in tag installation and the problem of tag invisibility are discussed. Then, taking into account both tag invisibility and tag installation, a pseudorandom tag arrangement is proposed, which is inspired from a Sudoku puzzle. It is shown that the proposed tag arrangement exhibits spatial randomness quite successively without increased difficulty in installation.

• 대한임베디드공학회논문지
• /
• 제4권2호
• /
• pp.69-78
• /
• 2009

Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

• 제어로봇시스템학회논문지
• /
• 제11권12호
• /
• pp.996-1001
• /
• 2005

Recently, with the development of service robots and with the new concept of ubiquitous world, the position estimation of mobile objects has been raised to an important problem. As pre-liminary research results, some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed in this paper. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter: 1. The RFID receiver gets the synchronization signal from the mobile robot and 2. The ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from. Three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can get the ultrasonic signals from only one or two beacons, because of the obstacles located along the moving path. Therefore, in this paper, as one of our dedicated contribution, the position estimation scheme with less than three sensors has been developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.