• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.480-487
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• 2009

Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.

• 대한임베디드공학회논문지
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• 제16권6호
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• pp.293-297
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• 2021

This paper presents how to create a 3D map and solve problems related to generating a global path planning for navigation. Map creation and localization were performed using the RTAB-Map package to create a 3D map of the environment. In addition, when the target point is within the obstacle space, the problem of not generating a global path was solved using the asr_navfn package. The performance of the proposed system is validated through experiments with a wheelchair-type robot.

• 제어로봇시스템학회논문지
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• 제17권4호
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.800-808
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• 2008

This paper presents a localization algorithm of the outdoor wheeled mobile robot using the sensor fusion method based on indirect Kalman filter(IKF). The wheeled mobile robot considered with in this paper is approximated to the two wheeled mobile robot. The mobile robot has the IMU and encoder sensor for inertia positioning system and GPS. Because the IMU and encoder sensor have bias errors, divergence of the estimated position from the measured data can occur when the mobile robot moves for a long time. Because of many natural and artificial conditions (i.e. atmosphere or GPS body itself), GPS has the maximum error about $10{\sim}20m$ when the mobile robot moves for a short time. Thus, the fusion algorithm of IMU, encoder sensor and GPS is needed. For the sensor fusion algorithm, we use IKF that estimates the errors of the position of the mobile robot. IKF proposed in this paper can be used other autonomous agents (i.e. UAV, UGV) because IKF in this paper use the position errors of the mobile robot. We can show the stability of the proposed sensor fusion method, using the fact that the covariance of error state of the IKF is bounded. To evaluate the performance of proposed algorithm, simulation and experimental results of IKF for the position(x-axis position, y-axis position, and yaw angle) of the outdoor wheeled mobile robot are presented.

• 한국전자통신학회논문지
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• 제17권4호
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• pp.687-694
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• 2022

본 논문에서는 Visual 동시적 위치추정 및 지도작성(SLAM : Simultaneous Localization and Mapping)기술을 응용하여 실내에서 생성된 SLAM 맵을 기반으로 지정된 목적지에 물건을 배달하는 자율주행 차량 플랫폼을 제안하였다. 실내에서 SLAM 맵을 생성하기 위해 소형 자율주행 차량 플랫폼의 상단에 SLAM 맵 생성을 위한 심도 카메라를 설치하고 SLAM 맵 속에서의 정확한 위치추정을 하기 위해 추적 카메라를 장착하여 구현하였다. 또한, 목적지의 표찰을 인식하기 위해 합성곱 신경망(CNN : Convolutional neural network)을 사용하여 목적지에 정확하게 도착할 수 있도록 주행 알고리즘을 적용하여 설계하였다. 실내 배송 자율주행 차량을 실제로 제작하였고 SLAM 맵의 정확도 확인과 CNN을 통한 목적지 표찰 인식 실험을 수행하였다. 결과적으로 표찰 인식의 성공률을 향상시켜 구현한 실내 배송용 자율주행 차량의 활용 적합성 여부를 확인하였다.

• 한국정보통신학회논문지
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• 제25권3호
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• pp.377-383
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• 2021

최근 4차 산업혁명에 따라 공장, 물류창고, 서비스영역에서 유연한 물류이송을 위한 자율 이동형 모바일 로봇의 사용이 증가하고 있다. 대규모 공장에서는 Simultaneous Localization and Mapping(SLAM)을 수행하기 위하여 많은 수작업이 필요하기 때문에 개선된 모바일 로봇 자율 주행에 대한 필요성이 대두되고 있다. 이에 따라 본 논문에서는 고정 및 이동 장애물을 피해 최적의 경로로 주행하는 Mapless Navigation에 대한 알고리즘을 제안하고자 한다. Mapless Navigation을 위하여 Deep Q Network(DQN)을 통해 고정 및 이동 장애물을 회피하도록 학습하였고 두 종류의 장애물 회피에 대하여 각각 정확도 90%, 93%를 얻었다. 또한 DQN은 많은 학습 시간을 필요로 하는데 이를 단축하기 위한 목표의 크기 변화 알고리즘을 제안하고 이를 시뮬레이션을 통하여 단축된 학습시간과 장애물 회피 성능을 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권4호
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.846-851
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• 2004

In this paper, we propose a global ultrasonic system for the self-localization and autonomous navigation of indoor mobile robots. The ultrasonic sensor is regarded as the most cost-effective ranging system among the possible alternatives, and it is widely used for general purpose, since it requires simple electronic drivers and has relatively high accuracy. The global ultrasonic system presented in this paper consists of four or more ultrasonic generators fixed at reference positions in the global coordinates of an indoor environment and two receivers mounted on the mobile robots. By using the RF (Radio Frequency) modules added to the ultrasonic sensors, the robot is able to control the ultrasonic generation and to obtain the critical distances from the reference positions, which are required in order to localize is position in the global coordinates. A kalman filter algorithm designed for the self-localization using the global ultrasonic system and the experimental results of the autonomous navigation are presented in this paper.

• 로봇학회논문지
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• 제11권2호
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• pp.60-72
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• 2016

This study proposes a multi-robot system, using multiple autonomous robots, to explore concrete structures and assist in their maintenance by sealing any cracks present in the structure. The proposed system employed a new self-localization method that is essential for autonomous robots, along with a visualization system to recognize the external environment and to detect and explore cracks efficiently. Moreover, more efficient crack search in an unknown environment became possible by arranging the robots into search areas divided depending on the surrounding situations. Operations with increased efficiency were also realized by overcoming the disadvantages of the infeasible logical behavioral model design with only six basic behavioral strategies based on distributed control-one of the methods to control swarm robots. Finally, this study investigated the efficiency of the proposed multi-robot system via basic sensor testing and simulation.