• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2895-2897
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• 2000

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm has two-layered hierarchical structure such as a lower layer for collision avoidance and goal approach. and upper layer for adaptive combination of these two algorithms. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective in stationary and moving obstacles environment.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.4-36
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• 2001

A robust and reliable path recognition system is one necessary component for the autonomous navigation of a mobile robot to help determining its current position in its navigation map. This paper describes a computer visual path-recognition system using on-board video camera as vision-based driving assistance for an autonomous navigation mobile robot. The common problem for a visual system is that its reliability was often influenced by different lighting conditions. Here, two different image processing methods for the path detection were developed to reduce the effect of the luminance: one is based on the RGB color model and features of the path, another is based on the HSV color model in the absence of luminance.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.84-89
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• 2014

In this paper, an image-based visual servo control strategy for tracking a target object is applied to a camera-mounted omni-directional mobile robot. In order to get target angular velocity of each wheel from image coordinates of the target object, in general, a mathematical image Jacobian matrix is built using a camera model and a mobile robot kinematics. Unlike to the well-known mathematical image Jacobian, a simple rule-based control strategy is proposed to generate target angular velocities of the wheels in conjunction with size of the target object captured in a camera image. A camera image is divided into several regions, and a pre-defined rule corresponding to the target-located image region is applied to generate target angular velocities of wheels. The proposed algorithm is easily implementable in that no mathematical description for image Jacobian is required and a small number of rules are sufficient for target tracking. Experimental results are presented with descriptions about the overall experimental system.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.578-584
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• 2015

In this study a moving platform for a mobile robot that can be traveling with a full automatic standing arm was developed. Conventional mobile robots generally may equip 4 wheels or 3 wheels with a caster wheel or independent driven wheels and have good statistic stability. When a mobile robot travels on a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it is sometimes physically impossible for the robot to go through the crossroad because of the size limit. The upright running mobile robot changes its posture to the upright posture which has a small planar area and is able to go through the crossroad. The upright control which was manually performed step by step before such as sequences of uprighting (returning), checking, and balancing, is now automated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.82-85
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• 2003

In this paper, in order to deduce the deep structure of a set of fuzzy rules from the surface structure, we use co-evolutionary algorithm based on modified Nash GA. This algorithm coevolves membership functions in antecedents and parameters in consequents of fuzzy rules. We demonstrate this co-evolutionary algorithm and apply to the mobile robot control. From the result of simulation, we compare modified Nash GA with the other co-evolution algorithms and verify the efficacy of this algorithm through application to fuzzy systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.309-312
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• 2005

본 논문에서는 비젼 시스템과 후각 센서를 이용하여 모바일 로봇의 냄새 발생지 탐색 기능을 구현 하였다. 모바일 로봇에서의 비젼 시스템은 많은 연구가 진행되어진 센싱 방식이지만, 후각 기능은 새롭게 지능 시스템의 센싱 방식으로 주목 받고 있는 추세이다. 이에 본 논문은 이전까지의 연구에서 보여준 임베디드 시스템에서의 가스 센싱 기능 구현을 벗어나 신경망 알고리즘을 이용하여 냄새를 구별 할 수 있는 후각 기능을 구현 하였으며, 비젼 시스템과 후각 센서의 복합적인 알고리즘을 통하여 냄새 발생지를 탐색하는 방법을 제시하였다. 또한 이를 실험하기 위해 AMOR(Autonomous Mobile Olfactory Robot)을 구현하여 남새 발생지 탐색 알고리즘의 효용성을 입증 하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.207-210
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• 2004

일반적인 이동 로봇의 주된 관심은 경로 생성과 생성된 경로 추종에 있다. 그러나 일부 고속의 이동성이 필요로 하는 로봇의 경우 동역학적 제한 조건이 존재하며, 이러한 제한 조건내에서 원하는 움직임에 대한 제어가 요구된다. 본 논문에서 환경 지도를 가지고 있지 않은 상태, 즉 미지의 환경에서 이동 로봇의 경로 추종에 있어서 빠른 이동시에 발생할 수 있는 이동 로봇의 미끄러짐이나 전복 현상을 막기 위해 이동 로봇의 동역학적 제한 조건을 퍼지 논리를 이용하여 기준 속도를 변화시켜 안전하고 빠른 경로 추종 성능을 얻고자 하였다. 특히, 라인 추종 이동 로봇을 모델링하여 실시간으로 변화하는 목표점에 대한 추종 제어기를 설계하고 퍼지 최적 속도 제한 제어기를 통해 연속적으로 변화하는 라인에 대해서 지능적으로 로봇이 변화하는 라인에 대해서 지능적으로 로봇의 속도를 제한하여 안정적인 추종 성능을 발휘함을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.179-184
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• 2002

Recently, internet-based applications can be found easily in various felds. Internet-based telerobot system becomes one of important applications of internet. Among many important technological issues on the internet-based telerobot, time-delay is inherently critical problem to be solved. Time-delay is classified as micro time-delay and macro time-delay in this paper. Algorithms for compensation of path-error and time-error are proposed for the both types of time-delays using fuzzy logic since fuzzy logic is one of the best tools to represent expert's knowledge. Simulation results show the validity of the proposed algorithms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.166-172
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• 2003

The dynamics of the DDWMR depends on the velocity difference of the two driving wheels. And which is known as a type of non-holonomic equation. By this reason, the treatment of DDWMR had become difficult and conservative. In this paper, the differential-driving wheeled mobile robot is considered. The Takaki-Surgeno fuzzy model and a control method for DDWMR is presented. The suggested controller has three control elements. The first element is fuzzy state feedback designed for eliminating the dependence of time-varying parameter. The second element is weighting controller which is designed for good frequency response. The third controller is PI-controller which is designed for good command following and robustness with un-modeled dynamics. In order for achieving the performance objective, the design of controller is based on the loop-shaping algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.370-372
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• 2008

본 연구에서는 이동 로봇에 영역 센서를 장착하여 실내에서 주변환경을 인식하여 지도를 작성하는 방법을 제안한다. 이동 로봇이 미지의 환경에서 자율 주행하기 위해서는 로봇 환경에 대한 지도를 작성하면서 이 지도 상에서 로봇의 위치를 인식할 수 있어야한다. 지도 작성과 위치 인식을 동시에 수행하는 SLAM을 구현하기위한 준비단계로서 본 논문에서는 일정한 시간 간격으로 연속적인 센서 신호들로 부터 동일 특징을 추출하고 이들을 서로 일치시켜서 로봇 이동 및 센서 신호에 불확실성이 있는 경우에도 지도를 작성하는 방법을 연구한다. 실제로 레이저 영역 센서를 장착한 이동 로봇을 이용하여 실내에서 지도를 작성하는 실험을 통하여 제안된 방법의 성능을 검증한다.