J. Gámez García

A machine vision system for defect characterization on transparent parts with non-plane surfaces

This contribution presents a machine vision system capable of revealing, detecting and characterizing defects on non-plane transparent surfaces. Because in this kind of surface, transparent and opaque defects can be found, special lighting conditions are required. Therefore, the cornerstone of this machine vision is the innovative lighting system developed. Thanks to this, the defect segmentation is straightforward and with a very low computational burden, allowing real-time inspection. To aid in the conception of the imaging conditions, the lighting system is completely described and also compared with other commercial lighting systems. In addition, for the defect segmentation, a new adaptive threshold selection algorithm is proposed. Finally, the system performance is assessed by conducting a series of tests using a commercial model of headlamp lens.This contribution presents a machine vision system capable of revealing, detecting and characterizing defects on non-plane transparent surfaces. Because in this kind of surface, transparent and opaque defects can be found, special lighting conditions are required. Therefore, the cornerstone of this machine vision is the innovative lighting system developed. Thanks to this, the defect segmentation is straightforward and with a very low computational burden, allowing real-time inspection. To aid in the conception of the imaging conditions, the lighting system is completely described and also compared with other commercial lighting systems. In addition, for the defect segmentation, a new adaptive threshold selection algorithm is proposed. Finally, the system performance is assessed by conducting a series of tests using a commercial model of headlamp lens.

A sensor planning system for automated headlamp lens inspection

Usually, the automated systems for quality control based on computer vision have been centered on the design of algorithms for detecting different types of defects. Nevertheless, the issues related to planning suitable sensor poses for the inspection task have received less attention. In addition, the applications where a vision sensor can only sample a portion of a part from a single viewpoint, the sensor planning problem becomes critically important. This is the case of the automated inspection of vehicle headlamp lens, that due to its geometry and dimensions, requires multiple sensor poses to observe the whole part. Moreover, the customer requirements that define the maximum defect size should also be taken into account in the inspection process. This paper presents a vision sensor planning system applied to the quality control of headlamp lenses. The system uses the lens CAD, a vision sensor model and the customer requirements, included through a fuzzy approach, to achieve an optimal set of viewpoints. To compute the number and distribution of the viewpoints, a genetic algorithm is used. Experimental results demonstrate the effectiveness of the sensor planning system on commercial lenses.

On-line system based on hyperspectral information to estimate acidity, moisture and peroxides in olive oil samples

We propose an on-line system to be applied in olive oil industry.We employ hyperspectral images for the prediction of olive oil parameters.Optimal wavelengths have been selected with different methods.We show the regression lines and the validation results. The analysis of the quality of virgin olive oil involves the determination of a series of properties, such as chemical indexes and organoleptic characteristics. In addition, the determination of these properties in real-time could be useful in order to improve the olive oil extraction process since the process parameters could be regulated with the real-time moisture information.In this paper, the feasibility of using a non-invasive hyperspectral device, in order to determine on-line three parameters of the olive oil (free acidity, peroxide index and moisture) is studied. In order to study the correlation between these parameters and the information obtained by the hyperspectral sensor (absorption level), three different methods were applied: genetic algorithms (GA), least absolute shrinkage and selection operator (LASSO), and successive projection algorithm (SPA). From the experimental results, reduced values in cross validation were obtained and the optimal wavelengths were pointed out.

Optimal Production Planning for the Virgin Olive Oil Elaboration Process

Abstract The quality and obtained quantity of Virgin Olive Oil is bounded by the characteristics of the olives to be processed, and further determined by the influence of the process variables during the actual elaboration. Since the quality of the olives evolves during the harvesting season, it is relevant to consider when to harvest the olives in order to maximize the profit over the whole season. This work proposes a method to determine an optimal production plan for the whole harvesting season and presents the results obtained in its application to four different scenarios.

A dynamic lighting system for automated visual inspection of headlamp lenses

This paper presents a novel lighting system to reveal surface defects on transparent parts with non-planar surface. Thanks to this system, the defect segmentation is straightforward and fast to compute and so a real-time inspection of these parts is possible. To aid in the conception of the imaging conditions, the lighting system is completely described and also a comparative study with others commercial lighting systems is done. Then, a new adaptive threshold selection algorithm for defect segmentation is proposed. Finally, the system performance is assessed using a commercial model of headlamp lens.

Decision Support System Based on Fuzzy Cognitive Maps and Run-to-Run Control for Global Set-Point Determination

The selection of the set points of the process variables plays a fundamental role in the final output of modern processes, as the quality characteristics of the final product and the performance metrics of the process are heavily influenced by these decisions. This paper presents a decision support system to determine these set points based on three components: a model of the system of interest based on the Fuzzy Cognitive Maps methodology, an optimization problem that provides the most appropriate actions to perform in each particular situation, and an observer that augments the optimization problem and allows to include feedback to the system, practically implementing a run-to-run control approach. A simple application example is included to illustrate the proposed approach.

Model predictive position/force control of an anthropomorphic robotic arm

When a robotic manipulator executes a task in restricted and unknown environments, it is necessary to implement a position/force control in free space and constrained space. In classic controllers, position/force control may be carried out by means a controller switching, once the contact point has been reached. In this paper, a new position/force predictive controller for an anthropomorphic robotic arm is proposed. This work proposes an unique control law for controlling both variables (position or force). In a model predictive framework, where several goals have to be reached, it is known that cost function includes several parameters (weights) whose modification allows to prioritize goals to achieve. This fact has been taken into account to set up the controller. The proposed control law is validated by experiments involving a 7-dof anthropomorphic robotic arm executing a trajectory tracking task in a restricted environment. As experimental results show, it is possible to control position and force by adjusting controller weights.

Visual Predictive Control of Robot Manipulators Using a 3D ToF Camera

This paper presents a visual servo strategy for an anthropomorphic manipulator with eye-to-hand configuration. As novelty, a time-of-flight (ToF) camera, together with a model-based predictive control (MPC), have been used to execute the manipulator tasks in an unstructured environment. The ToF camera provides 3-D data of a target object and the MPC cost function achieves convergence of robot motion. With this configuration, there is no requirement to estimate a 3-D feature point position from a 2-D image and the camera model. A procedure for the target segmentation on the depth data, which is based on a previous training, is also presented. Experimental results, obtained in a robotic platform, show that the proposed approach is well suited for visual servoing purposes.

High-accuracy automatic system to assemble vehicle headlamps

In this work, the conception, design and development of a prototype for the automatic assembly and dimensional correction of vehicle headlamps is presented. Firstly, we analyze different measurement systems that can be used to determine the position of the elements that compounds the headlamp; secondly, we show the main conclusions obtained from the application of different technologies of actuators used to control the position of the components during the assembly. Finally, it is described the experimental results which validate the proposed system. They were carried out in both the lab and the assembly line in the factory. The new prototype solve the problem of assembling vehicle headlamps obtaining a final product with minimum dimensional errors.

Image fusion for surface finishing inspection

This paper presents an automatic defect detection system for machined metallic surfaces. Depending on the type of surface treatment a characteristic texture may be added. The aim is to determine flaws even if their orientation and shape are very similar to the surface finishing. For this purpose, a procedure based on merging features obtained under different lighting conditions has been developed. All the devices involved in the image acquisition process are also detailed. Results of the automated inspection suggest that the system works effectively with a low value of false rejections. Finally, ways to further improve the defect detection rate have also been discussed.