Calibration of a Rotating Laser Range Finder using Intensity Features

© 2018 IEEE. This paper presents an algorithm for calibrating a '3D range sensor' constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process

Characterization of a RS-LiDAR for 3D Perception

High precision 3D LiDARs are still expensive and hard to acquire. This paper presents the characteristics of RS-LiDAR, a model of low-cost LiDAR with sufficient supplies, in comparison with VLP-16. The paper also provides a set of evaluations to analyze the characterizations and performances of LiDARs sensors. This work analyzes multiple properties, such as drift effects, distance effects, color effects and sensor orientation effects, in the context of 3D perception. By comparing with Velodyne LiDAR, we found RS-LiDAR as a cheaper and acquirable substitute of VLP-16 with similar efficiency.Comment: For ICRA201

Radial Velocity Prospects Current and Future: A White Paper Report prepared by the Study Analysis Group 8 for the Exoplanet Program Analysis Group (ExoPAG)

[Abridged] The Study Analysis Group 8 of the NASA Exoplanet Analysis Group was convened to assess the current capabilities and the future potential of the precise radial velocity (PRV) method to advance the NASA goal to "search for planetary bodies and Earth-like planets in orbit around other stars.: (U.S. National Space Policy, June 28, 2010). PRVs complement other exoplanet detection methods, for example offering a direct path to obtaining the bulk density and thus the structure and composition of transiting exoplanets. Our analysis builds upon previous community input, including the ExoPlanet Community Report chapter on radial velocities in 2008, the 2010 Decadal Survey of Astronomy, the Penn State Precise Radial Velocities Workshop response to the Decadal Survey in 2010, and the NSF Portfolio Review in 2012. The radial-velocity detection of exoplanets is strongly endorsed by both the Astro 2010 Decadal Survey "New Worlds, New Horizons" and the NSF Portfolio Review, and the community has recommended robust investment in PRVs. The demands on telescope time for the above mission support, especially for systems of small planets, will exceed the number of nights available using instruments now in operation by a factor of at least several for TESS alone. Pushing down towards true Earth twins will require more photons (i.e. larger telescopes), more stable spectrographs than are currently available, better calibration, and better correction for stellar jitter. We outline four hypothetical situations for PRV work necessary to meet NASA mission exoplanet science objectives.Comment: ExoPAG SAG 8 final report, 112 pages, fixed author name onl

Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard

This paper presents a novel method for fully automatic and convenient extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally printed chessboard. The proposed method is based on the 3D corner estimation of the chessboard from the sparse point cloud generated by one frame scan of the LiDAR. To estimate the corners, we formulate a full-scale model of the chessboard and fit it to the segmented 3D points of the chessboard. The model is fitted by optimizing the cost function under constraints of correlation between the reflectance intensity of laser and the color of the chessboard's patterns. Powell's method is introduced for resolving the discontinuity problem in optimization. The corners of the fitted model are considered as the 3D corners of the chessboard. Once the corners of the chessboard in the 3D point cloud are estimated, the extrinsic calibration of the two sensors is converted to a 3D-2D matching problem. The corresponding 3D-2D points are used to calculate the absolute pose of the two sensors with Unified Perspective-n-Point (UPnP). Further, the calculated parameters are regarded as initial values and are refined using the Levenberg-Marquardt method. The performance of the proposed corner detection method from the 3D point cloud is evaluated using simulations. The results of experiments, conducted on a Velodyne HDL-32e LiDAR and a Ladybug3 camera under the proposed re-projection error metric, qualitatively and quantitatively demonstrate the accuracy and stability of the final extrinsic calibration parameters.Comment: 20 pages, submitted to the journal of Remote Sensin

Calibration of scanning laser range cameras with applications for machine vision

Range images differ from conventional reflectance images because they give direct 3-D information about a scene. The last five years have seen a substantial increase in the use of range imaging technology in the areas of robotics, hazardous materials handling, and manufacturing. This has been fostered by a cost reduction of reliable range scanning products, resulting primarily from advanced development of computing resources. In addition, the improved performance of modern range cameras has spurred an interest in new calibrations which take account of their unconventional design. Calibration implies both modeling and a numerical technique for finding parameters within the model. Researchers often refer to spherical coordinates when modeling range cameras. Spherical coordinates, however, only approximate the behavior of the cameras. We seek, therefore, a more analytical approach based on analysis of the internal scanning mechanisms of the cameras. This research demonstrates that the Householder matrix [14] is a better tool for modeling these devices. We develop a general calibration technique which is both accurate and simple to implement. The method proposed here compares target points taken from range images to the known geometry of the target. The calibration is considered complete if the two point sets can be made to match closely in a least squares sense by iteratively modifying model parameters. The literature, fortunately, is replete with numerical algorithms suited to this task. We have selected the simplex algorithm because it is particularly well suited for solving systems with many unknown parameters. In the course of this research, we implement the proposed calibration. We will find that the error in the range image data can be reduced from more that 60 mm per point rms to less than 10 mm per point. We consider this result to be a success because analysis of the results shows the residual error of 10 mm is due solely to random noise in the range values, not from calibration. This implies that accuracy is limited only by the quality of the range measuring device inside the camera

Range Information Characterization of the Hokuyo UST-20LX LIDAR Sensor

This paper presents a study on the data measurements that the Hokuyo UST-20LX Laser Rangefinder produces, which compiles into an overall characterization of the LiDAR sensor relative to indoor environments. The range measurements, beam divergence, angular resolution, error effect due to some common painted and wooden surfaces, and the error due to target surface orientation are analyzed. It was shown that using a statistical average of sensor measurements provides a more accurate range measurement. It was also shown that the major source of errors for the Hokuyo UST-20LX sensor was caused by something that will be referred to as “mixed pixels”. Additional error sources are target surface material, and the range relative to the sensor. The purpose of this paper was twofold: (1) to describe a series of tests that can be performed to characterize various aspects of a LIDAR system from a user perspective, and (2) present a detailed characterization of the commonly-used Hokuyo UST-20LX LIDAR sensor

Study of optical techniques for the Ames unitary wind tunnels. Part 4: Model deformation

A survey of systems capable of model deformation measurements was conducted. The survey included stereo-cameras, scanners, and digitizers. Moire, holographic, and heterodyne interferometry techniques were also looked at. Stereo-cameras with passive or active targets are currently being deployed for model deformation measurements at NASA Ames and LaRC, Boeing, and ONERA. Scanners and digitizers are widely used in robotics, motion analysis, medicine, etc., and some of the scanner and digitizers can meet the model deformation requirements. Commercial stereo-cameras, scanners, and digitizers are being improved in accuracy, reliability, and ease of operation. A number of new systems are coming onto the market