On Solving Mirror Reflection in LIDAR Sensing

Yang, Shao-Wen; Wang, Chieh-Chih

doi:10.1109/tmech.2010.2040113

Cited by 47 publications

(33 citation statements)

References 13 publications

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“…Efforts have been made to automate the detection of mirror frames and to correct mirror reflection when using a laser sensor in robotics [25]. Additionally, mirrors have also been used for enhancing the 3D scanning of objects (i.e., cultural heritage) [26].…”

Section: Methodsmentioning

confidence: 99%

“…Actually, it is a popular topic in simultaneous localization and mapping (SLAM) [25]. The shadowing problem is not limited to the region under the scanner.…”

Section: Introductionmentioning

confidence: 99%

“…Actually, it is a popular topic in simultaneous localization and mapping (SLAM) [25]. Efforts have been made to automate the detection of mirror frames and to correct mirror reflection when using a laser sensor in robotics [25].…”

Section: Introductionmentioning

confidence: 99%

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Use of High-Quality and Common Commercial Mirrors for Scanning Close-Range Surfaces Using 3D Laser Scanners: A Laboratory Experiment

Riquelme

Mas

2017

Remote Sensing

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Three Dimension (3D) laser scanners enable the acquisition of millions of points of a visible object. Terrestrial laser scanners (TLS) are ground-based scanners, and nowadays the available instruments have the ability of rotating their sensor in two axes, capturing almost any point. Since many sensors can only operate in a vertical position, they cannot capture points located beneath themselves. Consequently, these instruments are generally unable to capture data in a vertical descending direction. Moreover, since the device positioning has certain requirements of space and terrain stability, it is possible that specific regions of interest are outside the reach of the laser. A possible solution is to address the laser beam towards the desired direction by means of a mirror. Common mirrors are very cheap; therefore, they are easy to manipulate and to substitute in case they get broken. However, due to their careless fabrication process, it seems reasonable to think that they are unprecise. In contrast, front-end mirrors are more expensive and delicate, and consequently, deflecting angles are more precise. In this research, we designed a laboratory test to analyze the arising noise when standard and high-quality mirrors are used during the TLS scanning process. The results show that the noise introduced when scanning through a standard mirror is higher than that produced when using a high-quality mirror. However, both cases show that this introduced error is lower than the instrumental error. As a result, this study concludes that it is reasonable to use standard mirrors when scanning in similar conditions to this laboratory test.

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Section: Methodsmentioning

confidence: 99%

“…Actually, it is a popular topic in simultaneous localization and mapping (SLAM) [25]. The shadowing problem is not limited to the region under the scanner.…”

Section: Introductionmentioning

confidence: 99%

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Use of High-Quality and Common Commercial Mirrors for Scanning Close-Range Surfaces Using 3D Laser Scanners: A Laboratory Experiment

Riquelme

Mas

2017

Remote Sensing

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“…For example, time of flight scanning systems that return multiple observations along the line of sight may return a weak signal reflected at the actual mirror surface. The presence of a framed mirror can also be inferred from the observed depth discontinuity (also called a jump edge) along the mirror-frame boundary [Käshammer and Nüchter 2015;Yang and Wang 2011].…”

Section: Detecting Planar Reflective Surfacesmentioning

confidence: 99%

Reconstructing scenes with mirror and glass surfaces

et al. 2018

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Fig. 1. Reconstructing a scene with mirrors. From left to right: Input color image showing the scanner with attached AprilTag in a mirror, reconstructed geometry without taking the mirrors into account, reconstruction taking the detected mirrors (rendered as cross-hatched area) into account and a photorealistic rendering of the scene including the mirrors. Detecting the mirrors is crucial for accurate geometry reconstruction and realistic rendering.Planar reflective surfaces such as glass and mirrors are notoriously hard to reconstruct for most current 3D scanning techniques. When treated naïvely, they introduce duplicate scene structures, effectively destroying the reconstruction altogether. Our key insight is that an easy to identify structure attached to the scanner-in our case an AprilTag-can yield reliable information about the existence and the geometry of glass and mirror surfaces in a scene. We introduce a fully automatic pipeline that allows us to reconstruct the geometry and extent of planar glass and mirror surfaces while being able to distinguish between the two. Furthermore, our system can automatically segment observations of multiple reflective surfaces in a scene based on their estimated planes and locations. In the proposed setup, minimal additional hardware is needed to create high-quality results. We demonstrate this using reconstructions of several scenes with a variety of real mirrors and glass.

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“…Mirrors are detected and tracked online, while resulting errors are recalculated only offline. In further research Yang et al (Yang and Wang, 2011) extended their algorithm for advanced mirror detection and identification of mirror images. The extended approach assumes each gap in the wall to be a specular reflective object.…”

Section: Related Workmentioning

confidence: 99%

Detection and Purging of Specular Reflective and Transparent Object Influences in 3d Range Measurements

Koch

May

Nüchter³

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3D-Reflection-Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It is more reliable in 3D as in 2D. Nevertheless, collect the data of multiple scans and post-filter them as soon as the object was bypassed should pursued. This is why future work concentrates on implementing a post-filter module. Besides, it is the aim to improve the discrimination between specular reflective and transparent objects.

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On Solving Mirror Reflection in LIDAR Sensing

Cited by 47 publications

References 13 publications

Use of High-Quality and Common Commercial Mirrors for Scanning Close-Range Surfaces Using 3D Laser Scanners: A Laboratory Experiment

Use of High-Quality and Common Commercial Mirrors for Scanning Close-Range Surfaces Using 3D Laser Scanners: A Laboratory Experiment

Reconstructing scenes with mirror and glass surfaces

Detection and Purging of Specular Reflective and Transparent Object Influences in 3d Range Measurements

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