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ABSTRACT: We propose a new classification algorithm, variance considered machine (VCM), by modifying optimal hyperplanes of the support vector machine (SVM). The SVM is a good method to calculate a slope of optimal hyperplanes with maximal margin. However, this algorithm neglects to consider variances and prior probabilities of the data. It can increase probabilities of error. To solve this problem, the VCM shifts the optimal hyperplanes of the SVM according to variances and prior probabilities. Therefore, the VCM has not only maximal margin, which is an advantage of the SVM, but also lower error probability. Through 10 case examples with different variances and prior probabilities, we demonstrated the superiority of the VCM by comparing the results of the SVM and VCM.
Industrial Electronics, 2009. ISIE 2009. IEEE International Symposium on; 08/2009
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ABSTRACT: In the moving of the mobile robot, the mobile robot acquires a map of its environment while simultaneously localizing itself relative to the map. Simultaneous localization ad mapping (SLAM) problems arise when the robot does not have access to a map of the environment, nor does it know its own pose. In this paper, we study the SLAM of mobile robot in the indoor environment with Digital Magnetic Compass and Ultrasonic Sensors. Digital Magnetic Compass has a strong feature against interference in the indoor environment better than compass which is can easily be disturbed by electromagnetic sources or large ferromagnetic structures. Ultrasonic Sensors are cheap and can give relatively accurate range readings. Autonomous mobile robot is aware of robot's moving direction and position by the restricted data. Also robot must localize as quickly as possible. As application for the SLAM on the autonomous mobile robot system, robot can find the localization and the mapping and can solve the Kid Napping situation for itself. Especially, in the Kid Napping situation, autonomous mobile robot use Ultrasonic sensors and Digital Magnetic Compass(DMC)'s data for moving. When robot receives the similar data by sensors, robot uses Computation Intelligence(CI) for perceiving in the robot's position.
Control, Automation and Systems, 2007. ICCAS '07. International Conference on; 11/2007
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Knowledge-Based Intelligent Information and Engineering Systems, 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007, Proceedings, Part III; 01/2007
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ABSTRACT: This paper deals with the creation of planetary gear trains including sensor for torque and rpm and the useful way to measure the torque and RPM of the geared motor. For this we have made the planetary geared reduction motor with Hall sensors and with the monitoring system. The monitoring system displays the sensing data (torque, rpm) and calculated data (power) and also has the network capability with Bluetooth protocol. We show that our solution is much more inexpensive and simple method to measure torque and rpm than before.
Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE; 12/2004
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ABSTRACT: Distributed autonomous robotic system (DARS) consists of central processing part, communication part, sensor part, and etc. It is essential for DARS, which is made of independent agents. Bluetooth is developed having the features as low power consumption, standard protocol, small module size and etc. So it is suitable for DARS. But it has some constraints like network structure, distance of communication, and so on. To overcome these constraints, more dynamic network system is needed for DARS. In this paper, we propose the self-organizable bluetooth network base on the routing-tree that is more adaptable for DARS. This network system is composed of the following four network-organization procedures-discovery, organization, maintenance, and re-organization (C. Chevallay et al., 2002). Also this system can operate in more dynamic environment and organize communication network by itself. By the reasons, this self-organizable bluetooth network is suitable for DARS and other dynamic environment.
Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE; 12/2004
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ABSTRACT: This paper presents a hexagon-based Q-leaning algorithm to find a hidden target object with multiple robots. An experimental environment was designed with five small mobile robots, obstacles, and a target object. Robots went in search of a target object while navigating in a hallway where obstacles were strategically placed. This experiment employed two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.
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ABSTRACT: This article describes the useful way to measure the torque and RPM of the geared motor. For this we have made the planetary geared reduction motor including 2 Hall sensors in it and the monitoring system. The monitoring system displays the sensing values (torque, rpm) and the calculated value (power) and it also has the network capability using the Bluetooth protocol. We will show that our solution is much more inexpensive and simple method to measure torque and rpm than before.
