CAD-model-based vision for space applications

A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs

A vision-based system for inspecting painted slates

Purpose – This paper describes the development of a novel automated vision system used to detect the visual defects on painted slates. Design/methodology/approach – The vision system that has been developed consists of two major components covering the opto-mechanical and algorithmical aspects of the system. The first component addresses issues including the mechanical implementation and interfacing the inspection system with the development of a fast image processing procedure able to identify visual defects present on the slate surface. Findings – The inspection system was developed on 400 slates to determine the threshold settings that give the best trade-off between no false positive triggers and correct defect identification. The developed system was tested on more than 300 fresh slates and the success rate for correct identification of acceptable and defective slates was 99.32 per cent for defect free slates based on 148 samples and 96.91 per cent for defective slates based on 162 samples. Practical implications – The experimental data indicates that automating the inspection of painted slates can be achieved and installation in a factory is a realistic target. Testing the devised inspection system in a factory-type environment was an important part of the development process as this enabled us to develop the mechanical system and the image processing algorithm able to perform slate inspection in an industrial environment. The overall performance of the system indicates that the proposed solution can be considered as a replacement for the existing manual inspection system. Originality/value – The development of a real-time automated system for inspecting painted slates proved to be a difficult task since the slate surface is dark coloured, glossy, has depth profile non-uniformities and is being transported at high speeds on a conveyor. In order to address these issues, the system described in this paper proposed a number of novel solutions including the illumination set-up and the development of multi-component image-processing inspection algorithm

Vision technology/algorithms for space robotics applications

The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed

Efficient completeness inspection using real-time 3D color reconstruction with a dual-laser triangulation system

In this chapter, we present the final system resulting from the European Project \u201d3DComplete\u201d aimed at creating a low-cost and flexible quality inspection system capable of capturing 2.5D color data for completeness inspection. The system uses a single color camera to capture at the same time 3D data with laser triangulation and color texture with a special projector of a narrow line of white light, which are then combined into a color 2.5D model in real-time. Many examples of completeness inspection tasks are reported which are extremely difficult to analyze with state-of-the-art 2D-based methods. Our system has been integrated into a real production environment, showing that completeness inspection incorporating 3D technology can be readily achieved in a short time at low costs

Separating Reflection and Transmission Images in the Wild

The reflections caused by common semi-reflectors, such as glass windows, can impact the performance of computer vision algorithms. State-of-the-art methods can remove reflections on synthetic data and in controlled scenarios. However, they are based on strong assumptions and do not generalize well to real-world images. Contrary to a common misconception, real-world images are challenging even when polarization information is used. We present a deep learning approach to separate the reflected and the transmitted components of the recorded irradiance, which explicitly uses the polarization properties of light. To train it, we introduce an accurate synthetic data generation pipeline, which simulates realistic reflections, including those generated by curved and non-ideal surfaces, non-static scenes, and high-dynamic-range scenes.Comment: accepted at ECCV 201

Automated Fiber Placement Defect Identity Cards: Cause, Anticipation, Existence, Significance, and Progression

Automated Fiber Placement (AFP), a major composite manufacturing process, can result in many defects during the layup process that often require manual corrective action to produce a part with acceptable quality. These defects are the main limitation of the technology and can be hard to categorize or define in many situations. This paper provides a thorough definition and classification of all AFP defects. This effort constitutes a comprehensive and extensive library relevant to AFP defects. The defects selected and defined in this work are based on understanding and experience from the manufacture and research of advanced composite structure. Proper classification of these defects required an in-depth literature review and consideration of various viewpoints ranging from designers, manufacturers, analysts, and inspection professionals. Collectively, these sources were utilized to develop the most accurate view of each of the individual defect types. The results are presented as identity cards for each defect type, intended to provide researchers and the manufacturing industry a clear understanding of the (1) cause, (2) anticipation, (3) existence, (4) significance, and (5) progression of the defined AFP defects. The link between AFP defects and process planning, layup strategies, and machining was also investigated. Categorization of all important automated fiber placement defects is presented