• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.287-292
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• 2024

The initial suppression of fires is critical to protecting human and material resources. In response to this, fire prevention and suppression systems using artificial intelligence and robot technology have recently been studied. In particular, an autonomous driving system that detects a fire using CNN is attracting attention. These systems respond quickly in the event of a fire, enabling initial fire suppression. However, since the conventional system is not equipped with a fire suppression function, direct intervention of firefighters is required. (1) To overcome these limitations, we propose an autonomous fire detection robot system equipped with a fire suppression function ROS-based firefighting system called 'ADEFS' (Autonomous-Detect & Extinguish-Fire Service). (2) The system performs three tasks to detect and extinguish. Tasks are to run the Ros-based SLAM Navigation, YOLO-CNN, and Four-degree freedom manipulator connected to the fire extinguishing pump. (3) Through this, early response in the event of a fire can minimize damage to life and property and can reduce labor costs, which can also be expected to reduce costs for companies.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.726-734
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• 2007

Generally, a mobile robot is moved by original input programs. However, it is very hard for a non-expert to change the program generating the moving path of a mobile robot, because he doesn't know almost the teaching command and operating method for driving the robot. Therefore, the teaching method with speech command for a handicapped person without hands or a non-expert without an expert knowledge to generate the path is required gradually. In this study, for easily teaching the moving path of the autonomous mobile robot, the autonomous mobile robot with the function of speech recognition is developed. The use of human voice as the teaching method provides more convenient user-interface for mobile robot. To implement the teaching function, the designed robot system is composed of three separated control modules, which are speech preprocessing module, DC servo motor control module, and main control module. In this study, we design and implement a speaker dependent isolated word recognition system for creating moving path of an autonomous mobile robot in the unknown environment. The system uses word-level Hidden Markov Models(HMM) for designated command vocabularies to control a mobile robot, and it has postprocessing by neural network according to the condition based on confidence score. As the spectral analysis method, we use a filter-bank analysis model to extract of features of the voice. The proposed word recognition system is tested using 33 Korean words for control of the mobile robot navigation, and we also evaluate the performance of navigation of a mobile robot using only voice command.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.320-327
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• 2006

This paper introduces a new entertainment robot called ELIRO-II(Eating Lizard RObot version 2)which is a bio-mimetic quadruped walking robot with autonomous eating function. We focus on the realization of the behavior of an animal, i.e., wandering around to find food and eating food. The ELIRO-II is modeled after a lizard, which has four legs, 2-DOF waist-joint, an eye part, a mouth part and a stomach part. The effectiveness of the developed robot is shown through real experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.336-345
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• 2011

In this paper, we introduce software development process for autonomous mobile robot with LEGO RCX. The software is designed from course analysis and a series of software design processes are applied for the development. Various control methods are devised to identify robot's location and to optimize the running strategy. To assure realtime property and reliability of the software, we adopted software engineering processes during the development. In this paper, we report the detailed software design processes and the implementation result that we have experienced with our practical LEGO robot platform.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1110-1115
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• 2004

Water covers two-thirds of the earth and has a great influence on the future existence of all human being. Thailand has extensive coastline and near shore water that contain vast biological and mineralogical resources. The rivers and canals can be found around the country especially in the Bangkok, which once called the Venice of the East. Autonomous underwater robot (AUR) will be soon a tool to help us better understand water resources and other environmental issues. This paper presents the design and basic control of a six-degree of freedom AUR "Chalawan", which was constructed to be used as a testbed for shallow. It is a simple low cost open-frame design, which can be modified easily to supports various research areas in the underwater environment. It was tested with a conventional proportional-integral-derivative (PID) controller. After fine-tuning of the controller gains, the results showed the controller's good performances. In the future, the dynamic model of the robot will be analyzed and identified. The advanced control algorithm will be implemented based on the obtained model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.323-326
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• 1995

During a fast decade, an automatic control technology makes an aggressive improvement with the developments of computer and communication technology. In large scale and complicated systems, an autonomous decentralized control system is required in which the sub-systems must have some ability such that the self-judgement and self-performance functions. In this paper, we propose an algorithm to realized these functions using micro mobile robot which is applied to a control of a werehouse. The proposed algorithm is based on performance index, and the selecting rules of the task between the sub-systems are induced by the index. Also, it is effected by weighting function which is determined by environment and kind of works. To verify the effectiveness of this algorithm, we develop the simulator to implement the autonomous decentralized control and apply to the micro mobile robot on the PC machine.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.155-162
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• 2003

We propose a new technique far real-tine controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Caussian function as a unit function in the fuzzy neural network. and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-foray. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1697-1700
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• 2003

We propose a new technique for real-time controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.25-28
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• 2002

The path planning of autonomous mobile robot use two method. One is global path planning and another is local path planning. In this paper, We study the local path planning of autonomous mobile robot move in unknown enviroment. This local path planning is based on neural network using the direction indicator rules learning. also the system is made up of sensor system. The motion control system for real-time execution. The experimental results show that the developed direction indicator system operates properly and strongly at circumstance.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3010-3012
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• 2000

In this paper. we suggest a vector fitness strategy for obstacle avoidance of autonomous mobile robot with genetic algorithm. Ordinary genetic algorithms provide not such a viable solution for autonomous running in a variant environment. because of the difficulty in fitness evaluation in real time. We show that the suggested method is efficient for the problem of autonomous mobile robot. Its control function evolves to adapt the varying environment. The experiment is done using the real mobile robot 'Khepera' with which we use a tournament genetic algorithm model with the Vectored Fitness Genetic Strategy.