Experimental review of distance sensors for indoor mapping
Midriem Mirdanies, Roni Permana Saputra

TL;DR
This paper experimentally compares Kinect, Hokuyo UTM-30LX, and RPLidar sensors for indoor mapping, analyzing their accuracy, error characteristics, and ability to detect transparent objects, providing insights for sensor selection.
Contribution
It offers a comprehensive experimental evaluation of three popular distance sensors, highlighting their strengths, weaknesses, and suitability for specific indoor mapping applications.
Findings
Hokuyo UTM-30LX has an average distance measurement error of 21.94 mm.
Kinect and RPLidar errors depend on object distance, with negative and positive correlations respectively.
Hokuyo UTM-30LX detects transparent objects beyond 200 mm, RPLidar cannot detect them at tested distances.
Abstract
In this paper, some of the distance sensor, including Kinect, Hokuyo UTM-30LX, and RPLidar were observed experimentally. Strengths and weaknesses of each sensor were reviewed so that it can be used as a reference for selecting a suitable sensor for any particular application. A software application has been developed in C programming language as a platform for gathering information for all tested sensors. According to the experiment results, it showed that Hokuyo UTM-30LX results in random normally distributed error on measuring distance with average error 21.94 mm and variance 32.11. On the other hand, error measurement resulted by Kinect and RPLidar strongly depended on measured distance of the object from the sensors, while measurement error resulted by Kinect had a negative correlation with the measured distance and the error resulted by RPLidar sensor had a positive correlation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
