• 한국전자통신학회논문지
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• 제7권2호
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• pp.425-431
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• 2012

로봇의 실외 주행의 경우 실내 주행과 달리 실외 환경 전체에 대한 지도를 미리 작성할 수 없어 대부분 GPS를 이용하고 있으며 지도에 기반한 연구는 거의 없는 상황이다. 본 논문에서는 경사 구간이 없는 2차원 평면의 실외환경에서 정밀 GPS를 사용하여 GPS 데이터를 MCL 알고리즘에 적용하여 실외 로봇 위치 추정을 구현하고, 이를 적용하여 간단한 임무 시나리오를 수행하였다. 그리고 미들웨어 기반의 OpenRTM을 적용하여 관리자가 서버를 통해 원격으로 로봇을 제어하거나 상황을 관제할 수 있도록 하였다.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.954-962
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• 2002

In a park or street, we can see many people jogging or walking with their dogs tracking their masters. In this study, an entertainment robot that imitates a dog's behavior is created. The robot's task is tracking a moving target that is recognized as the master. In order to design the robot, the ecological approach. in which the robot's goals and surroundings heavily influence its design, is used. A three-wheel type locomotion system is designed as the robot's physical structure which can follow a human jogging in outdoor space like a park. A sensor system which can detect the position of a master for the robot in the outdoor space, is developed. This sensor system consists of a signal transmitter which is at the hand of a master and some sensors which are mounted on the robot. The transmitter emits RF(radio frequency) and ultrasonic signals and the sensors detect the direction and distance from the robot to the transmitter by using the received signals. For the control architecture of the robot, a purely reactive behavior-based method is used in order to increase speed of response. The developed robot is evaluated through experiments conducted in indoor and outdoor environments.

• 제어로봇시스템학회논문지
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• 제16권4호
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• pp.361-367
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• 2010

This paper reports the development of a mobile robot for patrol using a single laser range finder. A Laser range finder is useful for outdoor environment regardless of illumination change or various weather conditions. In this paper we combined the motion control of the mobile robot and the algorithm for detecting the outdoor environment. For obstacle avoidance, we adopted the Vector Field Histogram algorithm. A laser range finder is mounted on the mobile robot and looking down the road with a small tilt angle. We propose an algorithm for detecting the surface of the road. The outdoor patrol robot platform is equipped with a DGPS system, a gyro-compass sensor, and a laser range finder. The proposed obstacle avoidance and road detection algorithms were experimentally tested in success.

• 제어로봇시스템학회논문지
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• 제17권9호
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• pp.916-921
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• 2011

Mobile robot localization is the task of estimating the robot pose in a given environment. This research deals with outdoor localization based on an elevation map. Since outdoor environments are large and contain many complex objects, it is difficult to robustly estimate the robot pose. This paper proposes a Hausdorff distance-based map matching method. The Hausdorff distance is exploited to measure the similarity between extracted features obtained from the robot and elevation map. The experiments and simulations show that the proposed Hausdorff distance-based map matching is useful for robust outdoor localization using an elevation map. Also, it can be easily applied to other probabilistic approaches such as a Markov localization method.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• 센서학회지
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• 제19권3호
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• 제어로봇시스템학회논문지
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• 제15권2호
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• pp.203-210
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• 2009

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

• 로봇학회논문지
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• 제5권2호
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• pp.135-142
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• 2010

Security robot has gradually developed and deployed in order to protect civilian's lives as well as fortune and subjugate the shortcomings of CCTV which lacks of mobility. We have developed a security robot for outdoor environment and the main purpose of the driving mechanism is to overcome the bumps or projections with high speed. The robot platform consists of 4 omnidirectional wheel-based driving mechanisms and suspension for each driving mechanism. In this paper, principal suspension parameters of outdoor security robot for overcoming obstacles with stability are studied and approximately optimized using Response Surface Methodology (RSM) since it is difficult to find the exact relationship between suspension parameters and the shock, which is significantly associated with stability of the robot, at the robot platform. Simulation using ADAMS is conducted for assessing the feasibility of optimized design parameters.

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

• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.585-593
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• 2006

In this paper, we propose a vision-based simultaneous localization and map-building (SLAM) algorithm. SLAM problem asks the location of mobile robot in the unknown environments. Therefore, this problem is one of the most important processes of mobile robots in the outdoor operation. To solve this problem, Extended Kalman filter (EKF) is widely used. However, this filter requires computational power (${\sim}O(N)$, N is the dimension of state vector). To reduce the computational complexity, we applied compressed extended Kalman filter (CEKF) to stereo image sequence. Moreover, because the mobile robots operate in the outdoor environments, we should estimate full d.o.f.s of mobile robot. To evaluate proposed SLAM algorithm, we performed the outdoor experiments. The experiment was performed by using new wheeled type mobile robot, Robhaz-6W. The performance results of CEKF SLAM are presented.