Zebedee: Design of a Spring-Mounted 3-D Range Sensor with Application to Mobile Mapping

Bosse, Michael; Zlot, Robert; Flick, Paul

doi:10.1109/tro.2012.2200990

Cited by 367 publications

(308 citation statements)

References 10 publications

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“…Zeb1 has been introduced by Bosse et al (2012) as a novel design of a 3D range sensor consisting of a 2D lidar scanner mounted on a flexible spring useful for 3-D perception in robotics and other mobile applications. They have demonstrated a particular realization of the general design concept, which is called Zebedee.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

Sırmaçek

Shen

Lindenbergh

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the requirements of the project, it is important to have a vision about what to expect from different sensors. In this paper, we provide a detailed analysis of the point clouds of the same room interior acquired from Zeb1 and Leica C10 sensors. First, it is visually assessed how different features appear in both the Zeb1 and Leica C10 point clouds. Next, a quantitative analysis is given by comparing local point density, local noise level and stability of local normals. Finally, a simple 3D room plan is extracted from both the Zeb1 and the Leica C10 point clouds and the lengths of constructed line segments connecting corners of the room are compared. The results show that Zeb1 is far superior in ease of data acquisition. No heavy handling, hardly no measurement planning and no point cloud registration is required from the operator. The resulting point cloud has a quality in the order of centimeters, which is fine for generating a 3D interior model of a building. Our results also clearly show that fine details of for example ornaments are invisible in the Zeb1 data. If point clouds with a quality in the order of millimeters are required, still a high-end laser scanner like the Leica C10 is required, in combination with a more sophisticated, time-consuming and elaborative data acquisition and processing approach.

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Section: Introductionmentioning

confidence: 99%

Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

Sırmaçek

Shen

Lindenbergh

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Figure 9 presents a resulting point cloud acquired with the backpack system in a long basement room. Bosse et al (2012) presented a seminal work about a Hokuyo laser scanner mounted on a spring system. The system is handheld, extremely lightweight and uses a nodding scanner motion to acquire 3D data.…”

Section: Semi-rigid Slam For Trajectory Optimizationmentioning

confidence: 99%

A Study of Scan Patterns for Mobile Mapping

Elsberg

Borrmann

Nüchter

2013

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

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ABSTRACT:Mobile terrestrial scanning systems automate terrestrial laser scanning. Continous scanning mobile terrestrial systems constantly spin the terrestrial laser scanner and thus combine terrestrial scanning with kinematic laser scanning. This paper presents a scan pattern analysis for these systems. We aim at finding the most advantageous combination of terrestrial and kinematic systems. The resulting 3D point cloud depends on the scan pattern and the trajectory and velocity of the mobile system.

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“…Furthermore, Structure from Motion (SfM) approaches, like Bundler (Snavely et al, 2008) or visual Simultaneous Localization and Mapping (SLAM) algorithms additionally handle the task of mapping in 3D by using images from single cameras (Engel et al, 2017), stereo cameras (Mur-Artal and Tardós, 2016) or Multi-Camera-Systems (MCSs) (Urban and Hinz, 2016). Instead of reconstructing the environment by utilizing visual observations, range measurements with laserscanners are practicable and can lead to dense and accurate results (Bosse et al, 2012;Weinmann et al, 2017). The manufacturers of laserscanners see market potential in UAVs and launched several light weight products like the RIEGL miniVUX-1UAV, the SICK TIM551 or the Hokuyo UTM-30LX-EW in recent years.…”

Section: Introductionmentioning

confidence: 99%

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

Hillemann

Jutzi²

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Unmanned Aerial Vehicle (UAV) with adequate sensors enable new applications in the scope between expensive, large-scale, aircraftcarried remote sensing and time-consuming, small-scale, terrestrial surveyings. To perform these applications, cameras and laserscanners are a good sensor combination, due to their complementary properties. To exploit this sensor combination the intrinsics and relative poses of the individual cameras and the relative poses of the cameras and the laserscanners have to be known. In this manuscript, we present a calibration methodology for the Unified Intrinsic and Extrinsic Calibration of a Multi-Camera-System and a Laserscanner (UCalMiCeL). The innovation of this methodology, which is an extension to the calibration of a single camera to a line laserscanner, is an unifying bundle adjustment step to ensure an optimal calibration of the entire sensor system. We use generic camera models, including pinhole, omnidirectional and fisheye cameras. For our approach, the laserscanner and each camera have to share a joint field of view, whereas the fields of view of the individual cameras may be disjoint. The calibration approach is tested with a sensor system consisting of two fisheye cameras and a line laserscanner with a range measuring accuracy of 30mm. We evaluate the estimated relative poses between the cameras quantitatively by using an additional calibration approach for Multi-Camera-Systems based on control points which are accurately measured by a motion capture system. In the experiments, our novel calibration method achieves a relative pose estimation with a deviation below 1.8• and 6.4mm.

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Zebedee: Design of a Spring-Mounted 3-D Range Sensor with Application to Mobile Mapping

Cited by 367 publications

References 10 publications

Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

A Study of Scan Patterns for Mobile Mapping

UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

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