BSA-CM: A Multi-robot Coverage Algorithm

González, Enríque; Gerlein, Eduardo A.

doi:10.1109/wi-iat.2009.182

Cited by 17 publications

(10 citation statements)

References 10 publications

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“…Research using MRCPP methods based on map decomposition has been conducted to improve the performance of the MRCPP method based on ant foraging. Most MRCPP methods based on map decomposition are classified into MRCPP methods [21]- [23] using boustrophedon decomposition [24], and MRCPP methods [9], [25]- [28] using a grid map.…”

Section: Related Workmentioning

confidence: 99%

“…In a previous CNP method, Gonzalez and Gerlein [9] provided a cooperative multi-agent system environment (BSA-CM), which is an MRCPP method based on the backtracking spiral algorithm (BSA) [42] using grid maps. In the BSA-CM method, each robot travels in a spiral path on the grid map.…”

Section: Related Workmentioning

confidence: 99%

“…The process of the previous MRCPP method is summarized in Fig. 1 [9], [10]. The three cleaning robots ( 1 , 2 , and 3 ) perform cleaning along a spiral [11] or zigzag path [12] in Fig.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Cleaning Robots Using Cleaning Distribution Method Based on Map Decomposition in Large Environments

Lee

Kang

2020

IEEE Access

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Most cleaning robots have a good cleaning performance for small environments such as houses but require a longer cleaning time due to problems such as slow cleaning progress and low battery capacity, making the robots unsuitable for large environments such as libraries and airports. Cleaning large environments with multiple robots is faster than cleaning them with a single robot. Multi-cleaning robots can utilize several robots to simultaneously clean and share the task of cleaning among the robots. However, as the number of robots increases and the effective distribution of cleaning is not efficient during the cleaning process, the cleaning time will consequently be longer due to the frequent collisions between the robots. Therefore, to shorten the cleaning time, multi-cleaning robots require a coverage path planning that uses an effective cleaning distribution method in the cleaning process. In this paper, a coverage path planning using a cleaning distribution method based on map decomposition is proposed to reduce the cleaning time of multi-cleaning robots. The experimental results demonstrated that the proposed multi-cleaning robots' coverage path planning could be used in large environments in the presence of several types of obstacles. Furthermore, the cleaning time was found to be shorter than that of the previous methods in the case of multi-cleaning robots. INDEX TERMS Coverage path planning, cleaning robot, computational efficiency, multi-robots system, robot path planning.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Multi-Cleaning Robots Using Cleaning Distribution Method Based on Map Decomposition in Large Environments

Lee

Kang

2020

IEEE Access

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“…Related work After a review of different approaches for multi-robot exploration, we conclude that the solutions are subscribed depend on the strategy chose for robots movement. Basically there are two types of movement or strategies [11]. The first type of strategies uses nonstructured trajectories [13 -17], where the navigation of the robots depends on the search of the best next point of view that drives in the elimination of borders of the unknown world, or, by means of probabilistic methods.…”

Section: IImentioning

confidence: 99%

Homogeneous Swarm Robots Exploration

Othman¹,

Rosli²,

Alhady³

2018

IJTSRD

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Exploration process in a real application seems had attracts the interest from researchers and academics nowadays. The usage of robots rather than human themselves give many benefit in term of security and safety, also in time and energy consumption. This project aims to generate a code represent the exploration technique in an unknown environment for homogeneous multi-agents systems. In multi-agents system, there are many variable involve in the result of the exploration process. The number of the agents, network connectivity, type of hardware, the environment and other aspects must be considered in multi-agents system exploration investigation. However, due to time constraint, this project only studies the effect of the number of robots or agents in the exploration task. The technique chose for the task must have a certain rules and assumptions to make the exploration process run smoothly and efficient. The code has been developed by using NetLogo due to the availability of sample models and toolboxes. Recording of the data was also done through the use of NetLogo. Finally, the data is arranged by using Microsoft Excel to extract the recorded data for analysis process. The usage of Minitab software is used to plot the graph. Hopefully, this system can be used in real application with the appropriate hardware.

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“…Ayrıca Gonzalez ve Gerlein çalışmalarında BSA algoritmasının geliştirilmiş halini sunmuşlardır [20]. Çok etmenli bir yaklaşımı temel alan ve robotun izleyeceği yolun kapsanmasını sağlayan çoklu robot platformu önermişlerdir.…”

Section: Introductionunclassified