• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.10 no.1
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• pp.369-376
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• 2005

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.2
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• pp.21-34
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• 2002

Different from ordinary mobile robots used in a well-structured industrial workspace, a guide mobile robot for the visually impaired should be designed in consideration of a moving obstacle, which mostly refers to pedestrians in intentional motions. Thus, the navigation of the guide robot can be facilitated if the intention of each detected obstacle can be known in advance. In this paper, we propose an inference method to understand an intention of a detected obstacle. In order to represent the environment with ultrasonic sensors, the fuzzy grid-type map is first constructed. Then, we detect the obstacle and infer the intention for collision avoidance with the CLA(Centroid of Largest Area) point of the fuzzy grid-type map. To verify the proposed method, some experiments are performed.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.577-582
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based Wheeled Mobile Robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps has a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. Data set between position of WMR and features of lamps are configured. Neural network are composed and teamed with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.9-18
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• 2013

In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.195-201
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• 2010

Recently, the necessity of the autonomous mobile robot is emphasized in order to enlarge the scope of activity and actively cope with the change of work environment. This paper proposes the algorithm which enables the mobile robot to avoid obstacles and lead it to the destination by the shortest path. And we verify the usability by a simulation. We made the algorithm with micro-GA and $\lambda$-geometry MRA. The area of simulation is limited to 320(width)$\times$200(length) pixels and one pixel is one centimeter. When we planned the path with only $\lambda$-geometry MRA, we could find the direction for path planning but could not find the shortest path. But when we planned the path with $\lambda$-geometry MRA and micro-GA, we could find the shortest path. So the algorithm enables us to find the direction for path planning and the shortest path.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.163-168
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• 2008

Navigation system based on indoor location estimation is one of the core technologies in mobile robot systems. Wireless sensor network has great potential in the indoor location estimation due to its characteristics such as low power consumption, low cost, and simplicity. In this paper we present an algorithm to estimate the indoor location of mobile robot based on wireless sensor network and fuzzy modeling. ZigBee-based sensor network usually uses RSSI(Received Signal Strength Indication) values to measure the distance between two sensor nodes, which are affected by signal distortion, reflection, channel fading, and path loss. Therefore we need a proper correction method to obtain accurate distance information with RSSI. We develop the fuzzy distance models based on RSSI values and an efficient algorithm to estimate the robot location which applies to the navigation algorithm incorporating the time-varying data of environmental conditions which are received from the wireless sensor network.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.245-254
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• 2008

Recently, many vision-based navigation methods have been introduced as an intelligent robot application. However, many of these methods mainly focus on finding an image in the database corresponding to a query image. Thus, if the environment changes, for example, objects moving in the environment, a robot is unlikely to find consistent corresponding points with one of the database images. To solve these problems, we propose a novel navigation strategy which uses fast motion estimation and a practical scene recognition scheme preparing the kidnapping problem, which is defined as the problem of re-localizing a mobile robot after it is undergone an unknown motion or visual occlusion. This algorithm is based on motion estimation by a camera to plan the next movement of a robot and an efficient outlier rejection algorithm for scene recognition. Experimental results demonstrate the capability of the vision-based autonomous navigation against dynamic environments.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.495-500
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• 2002

Recently, a service robot industry outstands as an up and coming industry of the next generation. Specially, there are so many research in self-steering movement(SSM). In order to implement SSM, robot must effectively recognize all around, detect objects and make a surrounding map with sensors. So, many robots have a sonar and a infrared sensor, etc. But, in these sensors, We only know informations about between the robot and the object as well as resolution faculty is of inferior quality. In this paper, we will introduce new algorithm that recognizes objects around robot and makes a two dimension surrounding map with a omni-direction vision camera and two stereo vision cameras.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.51-56
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• 2013

In order to apply a biped robot in real world, the robot requires a robust walking and a function of localization, path planning and navigation. Recently, localization and path planning using RFID of mobile robot has been studying. However, when the biped robot walks, it has unstability and tends to leave the path. In the paper we propose a method of walking stabilization using FSR(Force Sensing Resistor), Gyro and accelerometer for the real biped robot. Also a path tracking algorithm using RFID sensor attached in robot's foot is proposed based on localization of the robot. The proposed algorithm is verified from walking experiments using real biped robot on uneven terrain and path tracking experiments on the RFID environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.165-170
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• 2013

This paper proposes a method of simplification for robot simulation creation using functional concise script. General robotics simulation authoring tools require professional knowledge regarding development language and their APIs, and these prerequisites are considered as a big obstacle in implementing robotics simulation. In order to resolve these problems, we developed an authoring tool using functional concise script in building simulation environment, and this concise script composes of simplified service commands and minimum options. In experiment, we educated students and teachers in High school to use this authoring tool and we verified that the proposed method makes it possible to build robotics simulation environment and control simulated robots through one-day training course for the novices.