2019
DOI: 10.3390/app9153089
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A Low Overhead Mapping Scheme for Exploration and Representation in the Unknown Area

Abstract: The grid map, representing area information with the number of cells, is a widely used mapping scheme for mobile robots and simultaneous localization and mapping (SLAM) processes. However, the tremendous amount of cells in a grid map for a detailed map representation results in overheads for memory space and computing paths in mobile robots. Therefore, to overcome the overhead of the grid map, this study proposes a new low overhead mapping scheme which the authors call as the Rmap that represents an area with … Show more

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Cited by 4 publications
(16 citation statements)
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“…The exploration step indicates the number of goal points related to navigation simplicity and traversal path distance of the robot. In Table 2, we can see that the proposed IEFA spends minimum time and path distance for exploration in both environments compared to previous strategies [4,6]. In the cyclic environment, IEFA performed a 31% better path distance result than frontier-based path planning and 64% better than Rmap path-planning strategy.…”
Section: Experiments and Resultsmentioning
confidence: 91%
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“…The exploration step indicates the number of goal points related to navigation simplicity and traversal path distance of the robot. In Table 2, we can see that the proposed IEFA spends minimum time and path distance for exploration in both environments compared to previous strategies [4,6]. In the cyclic environment, IEFA performed a 31% better path distance result than frontier-based path planning and 64% better than Rmap path-planning strategy.…”
Section: Experiments and Resultsmentioning
confidence: 91%
“…The proposed algorithm is compared with two other exploration strategies. One of them uses cost-utility function to choose the optimal frontier proposed by Gomez [4], and the second strategy is the path-planning algorithm of Rmap exploration which was proposed by Lee [6]. All these three algorithms are evaluated in the same environments using the robot which is equipped as shown in Table 1.…”
Section: Experiments and Resultsmentioning
confidence: 99%
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