Seppe Sels

A Simple Evaluation Procedure for Range Camera Measurement Quality

Range cameras suffer from both systematic and random errors. We present a procedure to evaluate both types of error separately in one test. To quantify the systematic errors, we use an industrial robot to provide a ground truth motion of the range sensor. We present an error metric that compares this ground truth motion with the calculated motion, using the range data of the range sensor. The only item present in the scene is a white plane that we move in different positions during the experiment. This plane is used to compute the range sensor motion for the purpose of systematic error measurement, as well as to quantify the random error of the range sensor. As opposed to other range camera evaluation experiments this method does not require any extrinsic system calibration, high quality ground truth test scene or complicated test objects. Finally, we performed the experiment for three common Time-of-flight (TOF) cameras: Kinect One, Mesa SR4500 and IFM 03D303 and compare their performance.

New Error Measures for Evaluating Algorithms that Estimate the Motion of a Range Camera.

We compare the classical point-based algorithms for the extrinsic calibration of a range camera to the recent plane-based method. This method does not require any feature detection, and appears to perform well using a small number of planes (minimally 3). In order to evaluate the accuracy of the computed rigid motion we propose two new error metrics that get direct access to the ground truth provided by a mechanism with reliable motion control. Furthermore, these error metrics do not depend on an additional hand-eye calibration between the mechanism and the sensor. By means of our objective measures, we demonstrate that the planebased method outperforms the point-based methods that operate on 3-D or 2-D point correspondences. In our experiments we used two types of TOF cameras attached to a robot arm, but our evaluation tool applies to other sensors and moving systems.

Extrinsic Calibration of a Laser Galvanometric Setup and a Range Camera

Currently, galvanometric scanning systems (like the one used in a scanning laser Doppler vibrometer) rely on a planar calibration procedure between a two-dimensional (2D) camera and the laser galvanometric scanning system to automatically aim a laser beam at a particular point on an object. In the case of nonplanar or moving objects, this calibration is not sufficiently accurate anymore. In this work, a three-dimensional (3D) calibration procedure that uses a 3D range sensor is proposed. The 3D calibration is valid for all types of objects and retains its accuracy when objects are moved between subsequent measurement campaigns. The proposed 3D calibration uses a Non-Perspective-n-Point (NPnP) problem solution. The 3D range sensor is used to calculate the position of the object under test relative to the laser galvanometric system. With this extrinsic calibration, the laser galvanometric scanning system can automatically aim a laser beam to this object. In experiments, the mean accuracy of aiming the laser beam on an object is below 10 mm for 95% of the measurements. This achieved accuracy is mainly determined by the accuracy and resolution of the 3D range sensor. The new calibration method is significantly better than the original 2D calibration method, which in our setup achieves errors below 68 mm for 95% of the measurements.

Optimized robotic setup for automated active thermography using advanced path planning and visibility study

In-line inspection of advanced components remains a challenging task in industry. The authors will describe an automated methodology that uses numerical simulations to automatically determine the best set of experimental parameters to inspect the structure on defects using active thermography. The inspection is performed using a robotic arm and advanced path-planning tools to determine the optimal positions of the measurement points and excitation points. During the path planning, the directional emissivity is considered for the complex surface, and a minimization of the amount of measurement points is performed. The numerical simulation optimization used a genetic algorithm and spline regression model to optimize the heat power, robot speed, camera frame rate, and excitation timing to fulfill the automatic inspection.

Identification of pavement material properties using a scanning laser Doppler vibrometer

This paper presents an inverse modeling approach to estimate mechanical properties of asphalt concrete (i.e. Young’s modulus E, Poisson ratio ν and damping coefficients). Modal analysis was performed on an asphalt slab using a shaker to excite the specimen and an optical measurement system (a Scanning Laser Doppler Vibrometer or SLDV) to measure the velocity of a measurement grid on the surface of the slab. The SLDV has the ability to measure the vibration pattern of an object with high accuracy, short testing time and without making any contact. The measured data were used as inputs for a frequency domain model parameter estimation method (the Polymax estimator). Meanwhile, natural frequencies and damping ratios of the system were calculated using a Finite Element Modeling (FEM) method. Then, the Modal Assurance Criterion (MAC) was used to pair the mode shapes of the structure determined by measurements and estimated by FEM. By changing the inputs of the FEM analysis (E, ν and damping coefficients of the...

3D camera assisted fully automated calibration of scanning laser Doppler vibrometers

Scanning laser Doppler vibrometers (LDV) are used to measure full-field vibration shapes of products and structures. In most commercially available scanning laser Doppler vibrometer systems the user manually draws a grid of measurement locations on a 2D camera image of the product. The determination of the correct physical measurement locations can be a time consuming and diffcult task.In this paper we present a new methodology for product testing and quality control that integrates 3D imaging techniques with vibration measurements. This procedure allows to test prototypes in a shorter period because physical measurements locations will be located automatically.The proposed methodology uses a 3D time-of-flight camera to measure the location and orientation of the test-object. The 3D image of the time-of-flight camera is then matched with the 3D-CAD model of the object in which measurement locations are pre-defined.A time of flight camera operates strictly in the near infrared spectrum. To improve the sign...