• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.489-496
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• 2006

The random-based cleaning algorithm is a simple algorithm widely used in commercial vacuum cleaning robots. This algorithm has two limitations, that is, cleaning takes a long time and there is no guarantee that the cleaning will cover the whole cleaning area. This has lead to customer dissatisfaction. Thus, in recent years, many intelligent cleaning algorithms that takes into consideration information gathered from the cleaning area environment have been proposed. The plowing-based algorithm, which is the most efficient algorithm known to date when there are no obstacles in the cleaning area, has a deficiency that when obstacle prevail, its performance is not guaranteed. In this paper, we propose the Group-k algorithm that is efficient for that situation, that is, when obstacle prevail. The goal is not to complete the cleaning as soon as possible, but to clean the majority of the cleaning area as fast as possible. The motivation behind this is that areas close to obstacles are usually difficult for robots to handle, and hence, many require human assistance anyway In our approach, obstacles are grouped by the complexity of the obstacles, which we refer to as 'complex rank', and then decide the cleaning route based on this complex rank. Results from our simulation-based experiments show that although the cleaning completion time takes longer than the plowing-based algorithm, the Group-k algorithm cleans the majority of the cleaning area faster than the plowing algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.85-90
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• 2008

In this paper, we propose a new robot cleaning algorithm, which we call SetClean. The new algorithm cleans from the most less complex area. Sometimes, when the cleaning completion time can be longer or can not be estimated, cleaning larger area first is better than optimizing the whole time for cleaning. To do this, SetClean algorithm divides the whole area into cleanable sub-areas using Set Cover algorithm and cleans the area in the order of high efficiency that maximize the cleanable area per unit time. SetClean algorithm decides the navigation flow by considering not only the size of the area but also the distance from the current robot location to the area to be cleaned and the delay time caused by the number of turns within the area. The experimental results show the mechanism and performance of the SetClean algorithm.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.79-84
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• 2021

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.297-305
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• 2008

We present a cleaning robot algorithm that can be implemented on low-cost robot architecture while the cleaning performance far exceeds the conventional random style cleaning through human-robot interaction. We clarify the advantages and disadvantages of the two notable cleaning robot styles: the random and the mapping styles, and show the possibility how we can achieve the performance of the complicated mapping style under the random style-like robot architecture using the idea of human-aided cleaning algorithm. Experimental results are presented to show the performance.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.26-33
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• 2017

In this paper, we developed a control algorithm to maximize the cleaning performance and the cleaning efficiency of the underwater cleaning robot platform which has been developed for various cistern environment in the industrial field. Through these research and development, we have presented the operation and application of underwater cleaning robots that have been developed, and contributed to commercialization. Finally, this results were verified the effectiveness through actual field experiments.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.5
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• pp.187-194
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• 2020

This study presents the energy-saving sequential control algorithm to handle indoor CO₂ and PM2.5 for the improvement of the air quality of school classrooms. To solve indoor air quality (IAQ) problems, air cleaning and ventilation systems are mainly used for school classrooms. Although air cleaning is able to collect PM2.5, it is difficult to remove harmful gas substances. The ventilation system is suitable to tackle CO and CO₂, the volume ventilation, however, is relatively small. In this paper, to remove CO₂ and PM2.5, the pollutant balance equation for improving indoor air quality is reviewed. The sequential control algorithm of the ventilation and air cleaning system with four levels of criteria is introduced for the effective removal of pollutants. The proposed sequential control algorithm confirms that indoor CO₂ and PM2.5 can be properly controlled below the standard value. In addition, the sequential operation of air cleaning and ventilation systems has shown significant improvement in IAQ compared to the independent ventilation system operation. Particularly, such systems are efficient when outdoor PM2.5 is high.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.789-794
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• 2005

This paper describes an algorithm for minimal turning complete coverage Path planning for cleaning robots. This algorithm divides the whole cleaning area by cellular decomposition, and then provides the path planning among the cells employing a flow network. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The minimal turning of the robots is directly related to the faster motion and energy saving. The proposed algorithm is compared with previous approaches in simulation and the result shows the validity of the algorithm.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.252-254
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• 2005

Completer coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots and painter robots. In this paper, a novel Water Flowing Algorithm (WFA) is proposed for cleaning robots to complete coverage path planning in unknown environment without obstacles. The robot covers the whole workspace just like that water fills up a container. First the robot goes to the lowest point in the workspace just like water flows to the bottom of the container. At last the robot will come to highest point in the workspace just like water overflows from the container and simultaneously the robot has covered the whole workspace. The computer simulation results show that the proposed algorithm enable the robot to plan complete coverage paths.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.108.1-108
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• 2002

This paper is willing to propose a method of wall tracing, a moving algorithm between two points, when a Cleaning robot between two points moves. We use the information about obstacles and wall side in calculating different weight vector the each infrared sensors in cleaning robot. Therefore the cleaning robot navigates the wall. In the algorithm of wall tracing, the value of error in angle and distance between starting point and ending point should be zero to navigate the wall safely. The propriety of algorithm of the wall tracing is simulated as this method by using Visual C++. The result simulated proved to the simulation.