89,316 research outputs found
Topological model for machining of parts with complex shapes
Complex shapes are widely used to design products in several industries such
as aeronautics, automotive and domestic appliances. Several variations of their
curvatures and orientations generate difficulties during their manufacturing or
the machining of dies used in moulding, injection and forging. Analysis of
several parts highlights two levels of difficulties between three types of
shapes: prismatic parts with simple geometrical shapes, aeronautic structure
parts composed of several shallow pockets and forging dies composed of several
deep cavities which often contain protrusions. This paper mainly concerns High
Speed Machining (HSM) of these dies which represent the highest complexity
level because of the shapes' geometry and their topology. Five axes HSM is
generally required for such complex shaped parts but 3 axes machining can be
sufficient for dies. Evolutions in HSM CAM software and machine tools lead to
an important increase in time for machining preparation. Analysis stages of the
CAD model particularly induce this time increase which is required for a wise
choice of cutting tools and machining strategies. Assistance modules for
prismatic parts machining features identification in CAD models are widely
implemented in CAM software. In spite of the last CAM evolutions, these kinds
of CAM modules are undeveloped for aeronautical structure parts and forging
dies. Development of new CAM modules for the extraction of relevant machining
areas as well as the definition of the topological relations between these
areas must make it possible for the machining assistant to reduce the machining
preparation time. In this paper, a model developed for the description of
complex shape parts topology is presented. It is based on machining areas
extracted for the construction of geometrical features starting from CAD models
of the parts. As topology is described in order to assist machining assistant
during machining process generation, the difficulties associated with tasks he
carried out are analyzed at first. The topological model presented after is
based on the basic geometrical features extracted. Topological relations which
represent the framework of the model are defined between the basic geometrical
features which are gathered afterwards in macro-features. Approach used for the
identification of these macro-features is also presented in this paper.
Detailed application on the construction of the topological model of forging
dies is presented in the last part of the paper
Analysis and Observations from the First Amazon Picking Challenge
This paper presents a overview of the inaugural Amazon Picking Challenge
along with a summary of a survey conducted among the 26 participating teams.
The challenge goal was to design an autonomous robot to pick items from a
warehouse shelf. This task is currently performed by human workers, and there
is hope that robots can someday help increase efficiency and throughput while
lowering cost. We report on a 28-question survey posed to the teams to learn
about each team's background, mechanism design, perception apparatus, planning
and control approach. We identify trends in this data, correlate it with each
team's success in the competition, and discuss observations and lessons learned
based on survey results and the authors' personal experiences during the
challenge
VANET Applications: Hot Use Cases
Current challenges of car manufacturers are to make roads safe, to achieve
free flowing traffic with few congestions, and to reduce pollution by an
effective fuel use. To reach these goals, many improvements are performed
in-car, but more and more approaches rely on connected cars with communication
capabilities between cars, with an infrastructure, or with IoT devices.
Monitoring and coordinating vehicles allow then to compute intelligent ways of
transportation. Connected cars have introduced a new way of thinking cars - not
only as a mean for a driver to go from A to B, but as smart cars - a user
extension like the smartphone today. In this report, we introduce concepts and
specific vocabulary in order to classify current innovations or ideas on the
emerging topic of smart car. We present a graphical categorization showing this
evolution in function of the societal evolution. Different perspectives are
adopted: a vehicle-centric view, a vehicle-network view, and a user-centric
view; described by simple and complex use-cases and illustrated by a list of
emerging and current projects from the academic and industrial worlds. We
identified an empty space in innovation between the user and his car:
paradoxically even if they are both in interaction, they are separated through
different application uses. Future challenge is to interlace social concerns of
the user within an intelligent and efficient driving
Using computer vision in security applications
In this paper we present projects developed in the Computer Vision Laboratory, which address the issue of safety. First, we present the Internet Video Server (IVS) monitoring system [5] that sends live video stream over the Internet and enables remote camera control. Its extension GlobalView [1,6], which incorporates intuitive user interface for remote camera control, is based on panoramic image. Then we describe our method for automatic face detection [3] based on color segmentation and feature extraction. Finally, we introduce our SecurityAgent system [4] for automatic surveillance of observed location
By Design Not Default: Optimizing District Spending on Small High Schools
Analyzes small school design elements driving extra per-student spending, needed start-up and ramp-up investments, and impact on facility use and enrollment projections. Offers a tool for quantifying resource use and suggestions for effective allocation
Multimodal person recognition for human-vehicle interaction
Next-generation vehicles will undoubtedly feature biometric person recognition as part of an effort to improve the driving experience. Today's technology prevents such systems from operating satisfactorily under adverse conditions. A proposed framework for achieving person recognition successfully combines different biometric modalities, borne out in two case studies
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
Structure Preserving Large Imagery Reconstruction
With the explosive growth of web-based cameras and mobile devices, billions
of photographs are uploaded to the internet. We can trivially collect a huge
number of photo streams for various goals, such as image clustering, 3D scene
reconstruction, and other big data applications. However, such tasks are not
easy due to the fact the retrieved photos can have large variations in their
view perspectives, resolutions, lighting, noises, and distortions.
Fur-thermore, with the occlusion of unexpected objects like people, vehicles,
it is even more challenging to find feature correspondences and reconstruct
re-alistic scenes. In this paper, we propose a structure-based image completion
algorithm for object removal that produces visually plausible content with
consistent structure and scene texture. We use an edge matching technique to
infer the potential structure of the unknown region. Driven by the estimated
structure, texture synthesis is performed automatically along the estimated
curves. We evaluate the proposed method on different types of images: from
highly structured indoor environment to natural scenes. Our experimental
results demonstrate satisfactory performance that can be potentially used for
subsequent big data processing, such as image localization, object retrieval,
and scene reconstruction. Our experiments show that this approach achieves
favorable results that outperform existing state-of-the-art techniques
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