• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.151-169
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• 2014

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.221-222
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• 2023

The purpose of this study is to analyze the applicability and limitations of SPOT robots in the construction industry. The SPOT robot, which is being introduced to construction sites for smart construction with the progress of the 4th industrial revolution, is shaped like a four-legged dog and is equipped with various sensors for data collection and autonomous driving. In this study, hardware and software were analyzed, such as the size of the SPOT robot, mobility on slopes and heights, operating environment, and software functions that can collect data with a sensor weighing up to 14 kg. In addition, while the SPOT robot operates in a construction environment, performance such as stability, accuracy, signal connection distance, and obstacle avoidance are evaluated, and the applicability and limitations of the SPOT robot in the construction industry are analyzed. Based on this analysis, the purpose of this study is to evaluate when and how SPOT robots can be effectively used at construction sites, identify limitations, and derive contributions and improvements for the construction industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.396-401
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• 2016

Owing to developments in the internet of things, many products have developed and various researches have processed. Smart home systems in Internet of things area are receiving attention from many people than the other areas. Autonomous mobile robots perform various parts in many industries. In this paper, a smart housekeeping robot was implemented using internet of things and an autonomous mobile robot. In order to make a smart housekeeping robot, Raspberry Pi, wireless USB camera, and uBrain robot of Huins Corp. is used. To control the robot, cell-phone connected with IP of Raspberry Pi, and then Raspberry Pi connected with uBrain robot using Bluetooth. a smart housekeeping robot was controlled using commands of a cell-phone application. If some user wants to move a robot automatically, we implemented that a robot can be chosen an autonomous driving mode from the user. In addition, we checked a realtime video using a cell-phone and computer. This smart housekeeping robot can help user check their own homes in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.456-462
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• 2014

In this paper, we present a deployable bio-inspired robot called the Pillbot-light, which utilizes a safe autonomous navigation system. The Pillbot-light is mounted the station robot, and can be operated in a disaster relief operation or military operation. However, the Pilbot-light has a challenge to navigate autonomously because the Pilbot-light cannot be equipped with various sensors. As a result, we propose a new robot system for autonomous navigation that the station robot controls Pillbot-light equipped with vision camera and CPU of high performance. This system detects obstacles based on the edge extraction using vision camera. Also, it cannot only achieve path planning using the hazard cost function, but also localization using the Particle Filter. And this system is verified by simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.140-146
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• 2007

This paper demonstrates the development of a mobile robot for patrol. We fuse differential GPS, angle sensor and odometry data using the framework of extended Kalman filter to localize a mobile robot in outdoor environments. An important feature of road environment is the existence of curbs. So, we also propose an algorithm to find out the position of curbs from laser range finder data using Hough transform. The mobile robot builds the map of the curbs of roads and the map is used fur tracking and localization. The patrol robot system consists of a mobile robot and a control station. The mobile robot sends the image data from a camera to the control station. The remote control station receives and displays the image data. Also, the patrol robot system can be used in two modes, teleoperated or autonomous. In teleoperated mode, the teleoperator commands the mobile robot based on the image data. On the other hand, in autonomous mode, the mobile robot has to autonomously track the predefined waypoints. So, we have designed a path tracking controller to track the path. We have been able to confirm that the proposed algorithms show proper performances in outdoor environment through experiments in the road.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1269-1274
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• 2004

This paper presents a new quantisation algorithm which has the closed-loop form and guarantees the boundness of accumulative error. This algorithm is particularly useful for mobile robot navigation that is usually implemented on embedded systems. If wheel commands of the mobile robot are given by velocity or positional increment at every control instant and quantised due to finite word length of controller's CPU, the quantisation error gets accumulated to causes large position error. Such an error accumulative characteristic is fatal for non wheeled mobile robots or autonomous vehicles with non-holonomic constraint. To solve this problem, we propose a non-error accumulative quantisation algorithm with closed-loop form. We also show it can be extend to a generalized form corresponding to the n-th order accumulation. The boundness of the accumulative quantisation error is investigated by a series of computer simulation. The proposed method is particularly effective to precise navigation control the autonomous mobile robots.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1738-1745
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• 2016

In this paper, we present localization and autonomous navigation method using GPU(Graphics Processing Unit)-based SIFT(Scale-Invariant Feature Transform) algorithm and virtual force method for mobile robots. To do this, at first, we propose the localization method to recognize the landmark using the GPU-based SIFT algorithm and to update the position using extended Kalman filter. And then, we propose the A-star algorithm for path planning and the virtual force method for autonomous navigation of the mobile robot. Finally, we demonstrate the effectiveness and applicability of the proposed method through some experiments using the mobile robot with OPRoS(Open Platform for Robotic Services).

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.2
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• pp.115-126
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• 1996

In order to obtain the principal design data for developing the Autonomous Robot Vehicle(ARV), Sensitivity analysis on the trajectory error and friction force with respect to the dynamic parameters is performed. In the straight motion, the trajectory error has been proved to be much affected by the mass variance of the ARV while the lateral friction force is much affected by the location of the mass center. In the curved motion, the effect of mass and moment of inertia is considered importantly. In addition, the lateral offset gives more effect than the geometric dimension of the ARV on the trajectory errors and friction force.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.900-903
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• 1996

The objective of this paper is to make the weighted graph map for path planning using the ultrasonic sensor measurements that are acquired when an A.M.R (autonomous mobile robot) explores the unknown circumstance. First, The A.M.R navigates on unknown space with wall-following and gathers the sensor data from the environments. After this, we constructs the occupancy grid map by interpreting the gathered sensor data to occupancy probability. For the path planning of roadmap method, the weighted graph map is extracted from the occupancy grid map using morphological image processing and thinning algorithm. This methods is implemented on an A.M.R having a ultrasonic sensor.