• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.621-624
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• 2020

본 논문은 주행 로봇의 H/W에 관한 연구로서, 로봇 자체 지능을 통하여 주변 환경에 따라 변형되는 하이브리드 휠에 대한 바퀴 변형 방식을 제안한다. 더불어 바퀴 변형에 요구되는 다리의 개수, 극복 가능한 장애물의 높이, 계단주행 메커니즘을 구조적으로 분석하고, 개선된 성능을 입증하는 객관적인 실험데이터를 제시한다. 또한, 로봇 몸체 프레임을 설계하여 하이브리드 휠과 함께 장애물을 극복하는 응용 분야에 적용하여 제시한다.

• ICROS
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• v.18 no.2
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• pp.21-29
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• 2012

최근 자동차 연구개발에 있어 내연기관을 대체하는 친환경 자동차기술과 더불어 무인자동차, 자율주행기술이 많은 부분에서 시도되고 실현되어가고 있다. 지능형 자동차라는 개념에서 적용되었던 운전자안전보조시스템, 편의지원과 사고경감 시스템 등이 하나로 통합되어 무인자동차 기술로 발전하고 있다. 또 차량에 고가의 센서를 장착하여 주변환경이나 운전자를 모니터링하는 방식에서 IT 융합기술을 이용한 네트워크기술 (V2I, V2V, V2N & V2X)을 접목시키는 방안을 통하여 개개의 차량은 물론 교통체계의 전체적인 변화를 추구하고 있다. 이러한 첨단차량기술은 새로운 교통문화(차량공유시스템, 군집주행)의 개발과 또다른 교통체계의 연구로 확장되어가고 있다.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2058-2060
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• 2003

본 논문에서는 이동로봇의 실시간 영상처 리와 장애물 검출을 위한 알고리즘를 제시하였다. 단일 비젼 시스템을 사용하여 복도의 경계선을 추출하기 위하여 개선된 허프 트랜스폼 알고리즘을 적용하고 많은 연산량을 수행하기 위한 방법으로 레이져 포인터를 이용한 장애물 검출을 한다. 레이져 포인터의 레이져 빔이 장애물에 반사되어지는 정도를 영상처리를 통해 처리한 후 장애물의 유무를 판단하게 된다. 실험을 통하여 제시한 알고리즘의 우수성을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.202-207
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• 2013

In the paper, we design a autonomous mobile robot for freight transportation and propose an operation method of the robot in the warehouse. In order to implement autonomous navigation, it is needed to recognize the position of the robot and track the path to the target. Previous methods are hard to change the workspace environment and need high cost to install and keep a maintenance of the system. The lifter of freight transportation robot is designed to load and unload a baggage through up and down motion. Also, ultrasonic sensor, RFID, QR-code and camera sensor is used to carry out various functions while the robot navigates in the various environment. We design an operation method of the mobile robot in order to effectively arrive a goal position and transport a freight. The proposed methods are verified through various experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.8
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• pp.147-154
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• 2002

In this paper, a path navigation algorithm through use of a sensor platform is proposed. The sensor platform is composed of two electric motors which make panning and tilting motions. An algorithm for computing a real path and an obstacle length is developed by using a scanning method that controls rotation of the sensors on the platform. An Autonomous Robot Vehicle(ARV) can perceive the given path by adapting this algorithm. A sensor scanning method is applied to the sensor platform for using small numbers of sensor. The path navigation algorithm is composed of two parts. One is to perceive a path pattern, the other is used to avoid an obstacle. An optimal controller is designed for tracking the reference path which is generated by perceiving the path pattern. The ARV is operated using the optimal controller and the path navigation algorithm. Based on the results of actual experiments, this algorithm for an ARV proved sufficient for path navigation by small number of sensors and for a low cost controller by using the sensor platform with a scanning method.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.26-38
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• 2022

This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker).

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1231-1234
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• 2021

본 연구는 사람을 완전히 대체할 수 있는 완성형 서빙 로봇에 한 걸음 더 나아가는 것이 목표이다. 현재 시중에 나온 서빙 로봇은 호출 및 주문받기 등의 부가적인 기능을 할 수 없어 사람을 완전히 대체할 수 없다. 이에 따라 서빙 로봇의 효율성이 부족하여 대부분의 식당에서의 서빙 로봇 이용성이 낮다는 문제점이 있다. 따라서 호출 벨을 통한 로봇 호출 기능, 로봇에 부착된 인터페이스를 활용한 주문 및 결제 시스템 그리고 LIDAR 와 IMU 센서를 이용한 자율주행 기술을 이용하여 로봇만으로 다양한 업무를 수행할 수 있는 결과물을 만드는 것이 목표이다.