• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.61-69
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• 2010

An autonomous robot must have a global workspace map in order to cover the complete workspace. However, most previous coverage algorithms assume that they have a grid workspace map that is to be covered before running the task. For this reason, most coverage algorithms can not be applied to complete coverage tasks in unknown environments. An autonomous robot has to build a workspace map by itself for complete coverage in unknown environments. Thus, we propose a new DmaxCoverage algorithm that allows a robot to carry out a complete coverage task in unknown environments. This algorithm integrates a SLAM algorithm for simultaneous workspace map building. Experimentally, we verify that DmaxCoverage algorithm is more efficient than previous algorithms.

• 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.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2840-2842
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• 2000

This paper describes sensor-based occupancy grid map construction method through complete coverage navigation algorithm in unknown environment. In this paper, we use the updated Baysian model for probabilistic grid map. For map construction, complete coverage navigation method in which mobile robot can navigate complete field through as short path as possible in unknown environment, is used. The computer simulations result show that map construction method using complete coverage algorithm is efficient.

• 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.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2658-2679
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• 2018

This paper proposes a novel Random Scheduling Algorithm based on Subregion Coverage (RSASC), to solve the SET K-cover problem (an NP-complete problem). SET K-cover problem distributes the set of sensors into the maximum number of mutually exclusive subsets (MESSs) in such a way that each of them can be scheduled for lifetime extension of WSN. Sensor coverage divides the target region into different subregions. RSASC first sorts the subregions in the ascending order concerning their sensor coverage. Then, it forms the subregion groups according to their similar sensor coverage. Lastly, RSASC ensures the K-coverage of each subregion from every group by randomly scheduling the sensors. We consider the target-coverage and area-coverage applications of WSN to analyze the usefulness of our proposed RSASC algorithm. The distinct quality of RSASC is that it utilizes less number of deployed sensors (33% less) to form the optimum number of MESSs with the higher computational speed (saves more than 93% of the time) as compared to the existing three algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.73-80
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• 2009

This paper describes a path planning algorithm, which is the minimal turning path based on the shape and size of the cell to clean up the whole area with two cleaning robots. Our method divides the whole cleaning area with each cell by cellular decomposition, and then provides some path plans among of the robots to reduce the rate of energy consumption and cleaning time of it. In addition we suggest how to plan between the robots especially when they are cleaning in the same cell. Finally simulation results demonstrate the effectiveness of the algorithm in an unknown area with multiple robots. And then we compare the performance index of two algorithms such as total of turn, total of time.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.81-87
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• 2010

The coverage ability is one of essential techniques for the Robotic Vacuum Cleaner (RVC). Most of the RVCs rely on random or regular pattern movement to cover a target space due to the technical difficulties to implement localization and map and constraints of hardwares such as controller and sensors. In this paper, we consider two main issues which are low computational load and using sensors with very limited sensing capabilities. First, in our approach, computing procedures to build map and detect the RVC's position are minimized by simplifying data obtained from sensors. To reduce computational load, it needs simply presenting an environment with objects of various shapes. Another isuue mentioned above is regarded as one of the most important problems in our approach, because we consider that many RVCs use low-cost sensor systems such as an infrared sensor or ultrasonic sensor with limited capabilities in limited range, detection uncertainty, measurement noise, etc. Methods presented in this paper are able to apply to general RVCs equipped with these sensors. By both simulation and real experiment, we evaluate our method and verify that the proposed method guarantees a complete coverage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.96-116
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• 2016

Sensing coverage is a fundamental issue for Wireless Sensor Networks (WSNs). Several coverage configuration protocols have been developed; most of them presume the availability of precise knowledge about each node location via GPS receivers. However, equipping each sensor node with a GPS is very expensive in terms of both energy and cost. On the other hand, several GPS-less localization algorithms that aim at obtaining nodes locations with a low cost have been proposed. Although their deep correlation, sensing coverage and localization have long been treated separately. In this paper, we analyze, design and evaluate a novel integrated framework providing both localization and coverage guarantees for WSNs. We integrate the well-known Coverage Configuration Protocol CCP with an improved version of the localization algorithm AT-Dist. We enhanced the original specification of AT-Dist in order to guarantee the necessary localization accuracy required by CCP. In our proposed framework, a few number of nodes are assumed to know their exact positions and dynamically vary their transmission ranges. The remaining sensors positions are derived, as accurately as possible, using this little initial location information. All nodes positions (exact and derived) are then used as an input for the coverage module. Extensive simulation results show that, even with a very low anchor density, our proposal reaches the same performance and efficiency as the ideal CCP based on complete and precise knowledge of sensors coordinates.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2335-2337
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• 2001

In this paper, we address a new complete coverage navigation algorithm and guidance methodology for the cleaning robot. The proposed algorithm is based on the grid map. Six templates, excluding a Back-Trace(BT) template are used as the local navigation method. The effectiveness of the algorithm proposed in this paper is thoroughly demonstrated through simulations and the evaluation of parameters for the path execution.