• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.478-478
• /
• 2000

In this paper, presents the design of mobile field robot controlled by microcomputer. The computer works as the supervisory system for decision making and sending command to control the field robot. An information from encoder, infrared sensors using for control task of the robot that can be interconnected with the computer through the serial communication RS422 standard. In this case, the user can design the program algorithm base on microcomputer in order to control and define the routing of the mobile robot. Moreover, the robot can be installed other equipment fer collect data such as picture, sound, temperature etc., in order to working in the dangerous area.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.400-400
• /
• 2000

This paper purposed that verify the validity of Petri Net method for control progressive increase of system complexity, before extend the realized single robot system to multi-robot system. An autonomous mobile robot(AMR) needs decision making, motion control, path planning, tracking a path, obstacle avoidance, and sensor fusion, to complete its task. An AMR integrates and operates these technics through a consistent command system. An error in a command hierarchy which is like duplication or omission of a control command hierarchy for each module results in serious problems. This paper minimizes the error by modeling each module and whole system using Petri Net graphical representation and applies it to the exploration task of an AMR

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.165-167
• /
• 2011

Autonomous robots are intelligent machines that are capable of performing task in the world themselves with little or no human intervention. One of the main reason autonomous robots gained popularity in human's world is their ability to perform task with high degree of precision, accuracy and also consistency. One of the most studied fields in autonomous robot is the ability of decision making in robots. To tackle the ability of robots to make decision, this paper proposed an Autonomous Maze Solving Robot that is able to solve a maze using the optimum solution. The maze and the design of the robot are in compliance with IEEE Micromouse competition rules and regulation. Micromouse is an autonomous maze solving robot that shall be able to explore a maze on its own from a predefined starting location and find the optimum path to reach the predefined goal in the maze without human's intervention.

• The Journal of Korea Robotics Society
• /
• v.2 no.1
• /
• pp.48-54
• /
• 2007

A network-based robot [1] is a robot that explores service servers in the network environment for analyzing sensor data and making decision. Since network-based robot architecture was proposed, it's possible to reduce costs of robots. We hope robots would be all around at home environment. Therefore, normal users who are not experts need to be able to control those robots by using easy commands. We developed a scripting language, named CCSLR, to help users and developers who control various robots in ubiquitous environment. We focused on how to design the common language for various robots and how to translate a CCSLR script into a sequence of low-level commands of the target robot. In this paper, we propose scripting methods, with three layers. The CCSLR system reads the profile information from the knowledge representation database. Users don't have to know all about kinematical and mechanical details of a robot. Then again, the CCSLR system will use the profile information to translate the script into separated executable library commands. The CCSLR system manages robot's changing state every time a robot executes a command.

• Proceedings of the KIEE Conference
• /
• 2002.11c
• /
• pp.159-162
• /
• 2002

This paper presents a modified localization scheme of a mobile robot. When it navigates, the position error of a robot is increased and doesn't go to a goal point where the robot intends to go at the beginning. The objective of localization is to estimate the position of a robot precisely. Many algorithms were developed and still are being researched for localization of a mobile robot at present. Among them, a localization algorithm named continuous localization proposed by Schultz has some merits on real-time navigation and is easy to be implemented compared to other localization schemes. Continuous Localization (CL) is based on map-matching algorithm with global and local maps using only ultrasonic sensors for making grid maps. However, CL has some problems in the process of searching the best-scored-map, when it is applied to a mobile robot. We here propose fast and powerful map-matching algorithm for localization of a mobile robot by experiments.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.8
• /
• pp.98-103
• /
• 2019

A more accurate method of feature point extraction and matching for three-dimensional reconstruction using low-resolution images of crops is proposed herein. This method is important in basic computer vision. In addition to three-dimensional reconstruction from exact matching, map-making and camera location information such as simultaneous localization and mapping can be calculated. The results of this study suggest applicable methods for low-resolution images that produce accurate results. This is expected to contribute to a system that measures crop growth condition.

• Journal of Drive and Control
• /
• v.18 no.1
• /
• pp.31-38
• /
• 2021

This study presents a new principle for driving the robot aimed at reducing the position error for the boresonic examination of turbine rotor. The conventional method of inspection is performed by installing manipulator onto the flange of the turbine rotor and connecting a pipe, which is then being pushed into the bore. The longer the pipe gets, the greater sagging and distortion appear, making it difficult for the ultrasonic sensor to contact with the internal surface of the bore. A pneumatic pressure will ensure the front or rear feet of the robot in close contact with the inner wall to prevent slipping, while the ball screw on the body of the robot will rotate to drive it in the axial direction. The compression force required for tight contact was calculated in the form of a three-point support, and a static structural simulation analysis was performed by designing and modeling the robot mechanism. The driving performance and ultrasonic detection ability have been tested by fabricating the robot, the test piece for ultrasonic calibration and the transparent mock-up for robot demonstration. The tests have confirmed that no slipping occurs at a certain pneumatic pressure or over.

• Industrial Engineering and Management Systems
• /
• v.8 no.3
• /
• pp.181-193
• /
• 2009

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.1
• /
• pp.64-70
• /
• 2014

In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.12
• /
• pp.1079-1085
• /
• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.