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This paper presents a sensitivity analysis in the calibration of two sensors: a laser sensor Velodyne HDL-64E and a panoramic camera Point Grey Ladybug2; both sensors are used for three-dimensional urban reconstruction and were calibrated by two techniques; their results are compared in the sensitivity analysis. The effect of each parameter on the...
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... Model. A spherical global coordinate system whose origin is the LiDAR's center is defined as shown in Ref. [14]. The 3D data are generated using the function points3D ¼ f ðds; h; /Þ with reference to the laser origin, where ds is the distance to the object, h is the zenith angle, and / is the azi- muth angle, describing laser orientation, see Fig. 3. The mathe- matical model is based on the transformation of the 3D points in spherical coordinates to the Cartesian system as shown in the below ...
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Citations
Various sources of error can lead to the position accuracy of the robot being orders of magnitude worse than its repeatability. For the accuracy of drilling in the aviation field, high-precision assembly, and other areas depending on the industrial robot’s absolute positioning accuracy, it is essential to improve the accuracy of absolute positioning through calibration. In this paper, an error model of the robot considering both constant and high-order joint-dependent kinematic errors is established, and the model is modified by the Hermite polynomial, thereby mitigating the occurrence of the Runge phenomenon. To identify high-order joint-dependent kinematic errors, a robot calibration method based on the back-propagation neural network (BP) optimized by the sparrow search algorithm (SSA-BP) is proposed, which optimizes the uncertainty of weights and thresholds in the BP algorithm. Experiments on an EFORT ECR5 robot were implemented to validate the efficiency of the proposed method. The positioning error is reduced from 3.1704 mm to 0.2798 mm, and the error decrease rate reaches 42.92% (compared with BP calibration) and 21.09% (compared with particle swarm optimization back-propagation calibration). With the new calibration method using SSA-BP, robot positioning errors can be effectively compensated for, and the robot positioning accuracy can be improved significantly.
p>Despite autonomous navigation is one of the most proliferate applications of three-dimensional (3D) point clouds and imagery both techniques can potentially have many other applications. This work explores urban digitization tools applied to 3D geometry to perform urban tasks. We focus exclusively on compiling scientific research that merges mobile laser scanning (MLS) and imagery from vision systems. The major contribution of this review is to show the evolution of MLS combined with imagery in urban applications. We review systems used by public and private organizations to handle urban tasks such as historic preservation, roadside assistance, road infrastructure inventory, and public space study. The work pinpoints the potential and accuracy of data acquisition systems to handled both 3D point clouds and imagery data. We highlight potential future work regarding the detection of urban environment elements and to solve urban problems. This article concludes by discussing the major constraints and struggles of current systems that use MLS combined with imagery to perform urban tasks and to solve urban tasks.</p
