Geometric feature extraction from 2D laser range data for mobile robot navigation

Weerakoon, Tharindu; Ishii, Kazuo; Nassiraei, Amir Ali Forough

doi:10.1109/iciinfs.2015.7399032

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The threshold value equation utilized is consistent with the results of the Weerakoon et al [20] research. The residual error is 0.0038, whereas the angle (λ) is 8º.…”

Section: Adaptive Breakpoint Detector (Abd) and Iepfsupporting

confidence: 81%

“…Weerakoon et al [20] research's describes examples of ABD and Line Extraction implementation. The ABD threshold value equation was modified to Equation ( 5) in the research [20].…”

Section: ) Line Extractionmentioning

confidence: 99%

“…The tests were analyzed by comparing three Breakpoint Detector methods: the one we developed (ALTBD), the LT method, and the ABD IEPF method from the Weerakoon et al [20] research. In this research, the computing time, percentage of distance inaccuracy, and position difference between the Breakpoint Pattern Recognition results will be sought from each method.…”

Section: ) Testingmentioning

confidence: 99%

“…In his research on the ABD method, Su Young et al [19] identified the lack of a line cluster perpendicular to the sensor as a problem. The challenge was then solved by combining the ABD and LT methods to create the Dual Breakpoint Detector (DBD), and Weerakoon et al [20] also used ABD in their research. In order to increase the feature extraction rate value, Weerakoon et al [20] research suggests taking the measurement error value and the longest distance value into consideration.…”

Section: Introductionmentioning

confidence: 99%

“…The challenge was then solved by combining the ABD and LT methods to create the Dual Breakpoint Detector (DBD), and Weerakoon et al [20] also used ABD in their research. In order to increase the feature extraction rate value, Weerakoon et al [20] research suggests taking the measurement error value and the longest distance value into consideration. The corner breakpoint was determined in three phases in this investigation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Development of Adaptive Line Tracking Breakpoint Detection Algorithm for Room Sensing using LiDAR Sensor

Amin¹,

Priandana²,

Hardhienata³

2022

IJACSA

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This research focuses on the use of Light Detection and Ranging (LiDAR) sensors for robot localization. One of the most essential algorithms in LiDAR localization is the breakpoint detector algorithm which is used to determine the corner of the room. The previously developed breakpoint detection methods have weaknesses, such as the Adaptive Breakpoint Detector (ABD), could generate dynamic threshold values. The ABD results, on the other hand, still require Line Extraction to obtain the corner breakpoint. Line Extraction method, e.g. IterativeEnd Point Fit (IEPF), is used to categorize data, resulting in the generation of a line pattern as an interpretation of a wall. The computational method for obtaining the corner breakpoint becomes longer as the line is extracted. To address this issue, our algorithm proposes a new threshold area in the form of an ellipse with the threshold value parameter obtained from previously identified room size and sensor characteristics. As a result the corner breakpoint detection becomes more adaptive. The goal of this research is to create an Adaptive Line Tracking Breakpoint Detector (ALTBD) approach that will reduce the computing time required to detect corner breakpoints. Furthermore, the Line Extraction method required for corner breakpoint detection is modified in the ALTBD. To distinguish between the edge of the wall and the corner of the room, the boundary value is increased. The ALTBD method was tested in a simulation arena comprised of multiple rooms and halls. According to the results, the ALTBD computation time is faster in detecting corner breakpoints than the ABD IEPF method, also the accuracy for determining the position of the robot was improved.

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“…The threshold value equation utilized is consistent with the results of the Weerakoon et al [20] research. The residual error is 0.0038, whereas the angle (λ) is 8º.…”

Section: Adaptive Breakpoint Detector (Abd) and Iepfsupporting

confidence: 81%

“…Weerakoon et al [20] research's describes examples of ABD and Line Extraction implementation. The ABD threshold value equation was modified to Equation ( 5) in the research [20].…”

Section: ) Line Extractionmentioning

confidence: 99%

Section: ) Testingmentioning

confidence: 99%