Simulation-based comparison of 2D scan matching algorithms for different rangefinders

Li, Qiucheng; Müller, Fabian; Wenzel, Andreas; Rauschenbach, Thomas

doi:10.1109/mmar.2016.7575261

Cited by 3 publications

(1 citation statement)

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“…Many variants of ICP have been proposed, which affect all phases of the algorithm from the selection and matching of points to the minimization strategy. Q. C. Li, Muller, & Rauschenbach analyzes the ICP algorithm in detail and lists and compares the possible variants of each step [33]. ICP has very strong universality for aligning 3D models based purely on the geometry, and sometimes color, of the meshes.…”

Section: Motion Trackingmentioning

confidence: 99%

Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping

Zhao

Wang

et al. 2018

Remote Sensing

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High-precision indoor three-dimensional maps are a prerequisite for building information models, indoor location-based services, etc., but the indoor mapping solution is still in the stage of technological experiment and application scenario development. In this paper, indoor mapping equipment integrating a three-axis laser scanner and panoramic camera is designed, and the corresponding workflow and critical technologies are described. First, hardware design and software for controlling the operations and calibration of the spatial relationship between sensors are completed. Then, the trajectory of the carrier is evaluated by a simultaneous location and mapping framework, which includes reckoning of the real-time position and attitude of the carrier by a filter fusing the horizontally placed laser scanner data and inertial measurement data, as well as the global optimization by a closed-loop adjustment using a graph optimization algorithm. Finally, the 3D point clouds and panoramic images of the scene are reconstructed from two tilt-mounted laser scanners and the panoramic camera by synchronization of the position and attitude of the carrier. The experiment was carried out in a five-story library using the proposed prototype system; the results demonstrate accuracies of up to 3 cm for 2D maps, and up to 5 cm for 3D maps, and the produced point clouds and panoramic images can be utilized for modeling and further works related to large-scale indoor scenes. Therefore, the proposed system is an efficient and accurate solution for indoor 3D mapping.surveying process requires skilled personnel and sufficient knowledge of the survey area to pick optimal stations, good network design for marker placement, etc. [5][6][7][8].Mobile measurement technology integrates positioning, attitude determination, and measurement, which realizes the measurement in motion, improves the degrees of freedom of the measurement platform, and greatly reduces the time and labor costs. A typical mobile measurement system (MMS) consists of laser scanners, optical cameras, the global navigation satellite system (GNSS) and a high-grade inertial measurement unit (IMU) mounted on a vehicle. The trajectory of the vehicle is determined using GNSS and IMU, and the measurement results of scanners and cameras are reconstructed to a unified geographic frame by the relative position and attitude between units. The acquisition technology of large-scale outdoor point clouds using MMS has matured, and this type of system has been commercially available for several years and can achieve good accuracy [9][10][11][12]. Unfortunately, such a system cannot be directly used for indoor applications due to its reliance on GNSS, which obviously is not available indoors.With the boom of machine vision and the robotics industry, simultaneous location and mapping (SLAM) is extensively studied. SLAM solves the chicken-and-egg problem in an unknown environment by positioning according to the motion estimation and the existing map while simultaneously building an incrementa...

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Section: Motion Trackingmentioning

confidence: 99%