Getting On and Off an Elevator Safely for a Mobile Robot Using RGB-D Sensors

Kim, Ji‐Hwan; Jung, Minkuk; Song, Jae-Bok

doi:10.7746/jkros.2020.15.1.055

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…As a result of the experiment, the width of the boarding gate of the low-reflective elevator was 6.11 cm and the width of the boarding gate of the high-reflective elevator was 5.81 cm in terms of the maximum error rate. According to Kim, J., et al [8], a camerabased elevator recognition study was conducted on elevators with low-reflective and highreflective materials, and experiments were conducted from 0 to 30 degrees in 10-degree increments from facing the sensor to the front. The detection performance of elevators with low-reflective and high-reflective materials was confirmed with maximum position errors of 4.21 cm and 7.57 cm, respectively.…”

Section: Results Of the High-reflective Materials Gate Recognition Ex...mentioning

confidence: 99%

“…A study on depth-camera-based elevator recognition suggested a method of finding the exact location of the door using forward-oriented, three-dimensional distance data and particle filters for incorrect initial location of the elevator door. The experiment findings suggested that the average position error and angle error between the actual door position and the recognized position were 8 cm and 2 • or less, respectively [8].…”

Section: Introductionmentioning

confidence: 92%

“…Recent studies on elevator recognition include those examining depth-camera-based elevator recognition and strong elevator door recognition using an LRF (laser range finder) and cameras [8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…Existing elevator recognition studies used LiDAR sensors that measure fast and accurate distance values to solve the inconvenience of maintenance and repair, which is a limitation of elevator recognition using Marker [8][9][10][11]. Since LiDAR sensors measure distances using light sources, the reliability of the measured distance data is determined by the type of surface material measured [14].…”

Section: Introductionmentioning

confidence: 99%

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Study on Elevator Recognition Techniques for Upper-Limb-Disabled Wheelchair Users

Kim,

Eom,

Lee

2023

Applied Sciences

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This study proposes a LiDAR-sensor-based elevator recognition technique to prevent collisions caused by poor operation and the cognitive decline of wheelchair users with upper limb disabilities. Existing elevator recognition studies show high performance for elevator door recognition, but this can only be recognized at a position where the elevator can be viewed directly due to the angle of view range of the sensor. This is not appropriate for wheelchair users who are inexperienced in operation because alignment must be performed directly based on the elevator. Therefore, this study presents a LiDAR-sensor-based elevator recognition technique that can detect elevators from the side to the position and at an angle to the front in order to solve this problem. In addition, this study proposes a technique for recognizing elevator gates finished with low- and high-reflective materials in order to enable recognition in various elevator environments. In order to quantitatively verify the elevator recognition technique proposed in this study, experiments were conducted in an elevator environment consisting of low and high reflections. The results of the experiments confirmed that there was no problem in applying the wheelchair active driving technique.

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Section: Results Of the High-reflective Materials Gate Recognition Ex...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%