• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.845-850
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• 2009

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.32.6-32
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• 2001

This paper describes the steering control and geomagnetism cancellation for an autonomous mobile robotusing MR sensors. The magnetic-resistive (MR) sensor obtains the vector summation of the magnetic fields from embedded magnets and the Earth. The robot is controlled by the magnetic fields from embedded magnets. So, geomagnetism is the disturbance in the steering control system. In this paper, we propose a new method of the sensor arrangement in order to remove the geomagnetism and robotbody interference. The proposed method uses two MR sensors located in a level plane and the steering controller has been developed. The controller has three input variables (dBx, dBy, dBz) using the measured magnetic field difference, and an output variable (the steering angle) ...

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.1-9
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• 2022

With the development of artificial intelligence, many studies have focused on evaluating abnormal situations by using various sensors, as industries try to automate some of the surveillance and security tasks traditionally performed by humans. In particular, mobile robots using multimodal sensors are being used for pilot operations aimed at helping security robots cope with various outdoor situations. Multiagent systems, which combine fixed and mobile systems, can provide more efficient coverage (than that provided by other systems), but network bottlenecks resulting from increased data processing and communication are encountered. In this report, we will examine recent trends in object recognition and abnormal-situation determination in various changing outdoor security robot environments, and describe an outdoor security robot platform that operates as a multiagent equipped with a multimodal sensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.330-336
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• 2005

Existing Bayesian update method using ultrasonic sensors only for mobile robot map building has a problem of the quality of map being degraded in the wall with irregularity, which is caused by the wide beam distribution. For improving this problem, an infrared sensors aided map building method is presented in this paper. Information of obstacle at each region in ultrasonic sensor beam is acquired using the infrared sensors and the information is used to get the confidence of ultrasonic sensor information via fuzzy inference system and genetic algorithm. Combining the resulting confidence with the result of Bayesian update method, an improve map is constructed. The proposed method showed good results in the simulations and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.605-613
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• 2013

This research proposes a vibration pattern algorithm to implement the haptic joystick to control a mobile robot at the remote site without watching the navigation environment. When the user cannot watch the navigation environment of the mobile robot, the user may rely on the haptic joystick solely to avoid obstacles and to guide the mobile robot to the target. To generate vibration patterns, there is a vibration motor at the bottom of the joystick which is held by the user to control the motion direction of the mobile robot remotely. When the mobile robot approaches to an obstacle, a pattern of vibration is generated by the motor, and by feeling the vibration pattern which is determined by the relative position of the mobile robot to the obstacle, the user can move the joystick to avoid the collision to the obstacle for the mobile robot. To generate the vibration patterns to convey the relative location of the obstacle near the mobile robot to the user, Fuzzy interferences have been utilized. To measure the distance and location of the obstacle near the mobile robot, ultrasonic sensors with the ring structure have been adopted and they are attached at the front and back sides of the mobile robot. The precise location of the obstacle is obtained by fusing the multiple data from ultrasonic sensors. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.949-955
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• 2007

This paper proposes an efficient localization algorithm in the RFID sensor space for the precise localization of a mobile robot. The RFID sensor space consists of embedded sensors and a mobile robot. The embedded sensors, that is tags are holding the absolute position data and provide them to the robot which carries a reader and requests the absolute position fur localization. The reader, it is called as antenna usually, gets several tag data at the same time within its readable range. It takes time to read all the tags and to process the data to estimate the position, which is a major factor to deteriorate the localization accuracy. In this paper, an efficient algorithm to estimate the position and orientation of the mobile robot as quickly as possible has been proposed. Along with the algorithm, a new allocation of the tags in the RFID sensor space is also proposed to improve the localization accuracy. The proposed algorithms are demonstrated and verified through the real experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.440-447
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• 2018

Double parking is very common in a parking lot where there is not sufficient parking space. When we double-park a car, we leave transmission gear in neutral position and release the emergency brake so that the double-parked car can be moved just by pushing it. However, moving a double-parked car by pushing is very hard and dangerous especially for the old and the weak. So, we propose an omni-directional mobile robot for moving a double-parked car easily and safely. The developed omni-directional mobile robot moves a double-parked car by rotating a wheel of a double-parked car. It has two specially designed rollers to rotate a wheel of a double-parked car and is designed so that the height of the robot is very low to be able to enter beneath a double-parked car. It can move a double-parked car safely by detecting obstacles in the way with five ultrasonic sensors. We verified by several experiments that the developed omni-directional mobile robot can be used to move a double-parked car easily and safely.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.288-289
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• 2018

The use of IoT (Internet of Things) is rapidly expanding to enhance the quality of life as seen in the interconnection between mobile devices and Web. This paper proposes an embedded system that connects sensors and mobile devices via IoT technology, improving the user's ability and service experience to remotely control the home appliances with mobile-detection features. Home appliances are expected to increase labor efficiency by utilizing the embedded system connected to the sensors. Using mobile applications to control home appliances remotely and to monitor operation status advances the user's knowledge, experience, and perspectives to experience refined life qualities.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.304-313
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• 2005

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robot need to recognize his position and direction for intelligent performance in an unknown environment. And the mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. Notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this research, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the accurate measurement. As a general approach of sensor fusion, a UT -Based Sensor Fusion(UTSF) scheme using Unscented Transformation(UT) is proposed for either joint or disjoint data structure and applied to the landmark identification for mobile robot navigation. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations and experiments. The newly proposed, UT-Based UTSF scheme is applied to the navigation of a mobile robot in an unstructured environment as well as structured environment, and its performance is verified by the computer simulation and the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.137-143
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• 2005

Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.