Camera Calibration with Weighted Direct Linear Transformation and Anisotropic Uncertainties of Image Control Points

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with a conveyor belt, robot and an industrial color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of type A standard uncertainty and type B standard uncertainty, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e., measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

Section: Resultsmentioning

confidence: 99%

Intelligent Dynamic Identification Technique of Industrial Products in a Robotic Workplace

Vachálek

Šišmišová

Vašek

et al. 2021

“…The motion estimation of 3D points is dealt with using perspective-n-point (PnP) [46] or iterative close point (ICP) [47]. Several approaches have been proposed to solve PnP and ICP [48], including direct linear transformation (DLT) [49] and singular value decomposition (SVD) [50].…”

Section: Vision Combined With Depth Informationmentioning

confidence: 99%

An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation

Yang

Zhang

et al. 2021

Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents. In spite of the high performance of the single-sensor navigation method, multi-sensor fusion methods still potentially improve the perception and navigation abilities of mobile agents. This work summarizes the multi-sensor fusion methods for mobile agents’ navigation by: (1) analyzing and comparing the advantages and disadvantages of a single sensor in the task of navigation; (2) introducing the mainstream technologies of multi-sensor fusion methods, including various combinations of sensors and several widely recognized multi-modal sensor datasets. Finally, we discuss the possible technique trends of multi-sensor fusion methods, especially its technique challenges in practical navigation environments.

“…Currently, there are many methods proposed to solve this problem. Among these, the DLT [14,15] method is classical and efficient but vulnerable to noise interference and has poor robustness. Li et al have proposed an RPnP [16] method, which can always present stable calculation results regardless of the number of feature points, but it cannot get a unique solution when using the least square error, and its solving accuracy needs to be improved.…”

Section: Introductionmentioning

confidence: 99%

Pose Determination of the Disc Cutter Holder of Shield Machine Based on Monocular Vision

Peng

Zhu

Zhang

et al. 2022

The visual measurement system plays a vital role in the disc cutter changing robot of the shield machine, and its accuracy directly determines the success rate of the disc cutter grasping. However, the actual industrial environment with strong noise brings a great challenge to the pose measurement methods. The existing methods are difficult to meet the required accuracy of pose measurement based on machine vision under the disc cutter changing conditions. To solve this problem, we propose a monocular visual pose measurement method consisting of the high precision optimal solution to the PnP problem (OPnP) method and the highly robust distance matching (DM) method. First, the OPnP method is used to calculate the rough pose of the shield machine’s cutter holder, and then the DM method is used to measure its pose accurately. Simulation results show that the proposed monocular measurement method has better accuracy and robustness than the several mainstream PnP methods. The experimental results also show that the maximum error of the proposed method is 0.28° in the direction of rotation and 0.32 mm in the direction of translation, which can meet the measurement accuracy requirement of the vision system of the disc cutter changing robot in practical engineering application.