Abstract

Abstract
Reliable operation of production lines without unscheduled disruptions is of paramount importance for ensuring the proper operation of automated working cells involving robotic systems. This article addresses the issue of preventing disruptions to an automotive production line that can arise from incorrect placement of aluminum car parts by a human operator in a feeding container with 4 indexing pins for each part. The detection of the misplaced parts is critical for avoiding collisions between the containers and a high pressure washing machine and also to avoid collisions between the parts and a robotic arm that is feeding parts to a air leakage inspection machine. The proposed inspection system relies on a 3D sensor for scanning the parts inside a container and then estimates the 6 DoF pose of the container followed by an analysis of the overlap percentage between each part reference point cloud and the 3D sensor data. When the overlap percentage is below a given threshold, the part is considered as misplaced and the operator is alerted to fix the part placement in the container. The deployment of the inspection system on an automotive production line for 22 weeks has shown promising results by avoiding 18 hours of disruptions, since it detected 407 containers having misplaced parts in 4524 inspections, from which 12 were false negatives, while no false positives were reported, which allowed the elimination of disruptions to the production line at the cost of manual reinspection of 0.27% of false negative containers by the operator.

Abstract

Abstract
The 5dpo team presented a solid set of innovative solutions. The overall workings of the team are presented. Mechanical and electronic solutions are explained and closed loop working is discussed. Main innovative features include I-R communications link and circular bar code for robot tracking. Low level control now presents a dynamics prediction layer for enhanced motion control. Team strategy is also new and a multi-layered high level reasoning system based on state charts allows for cooperative game play. © 2002 Springer-Verlag Berlin Heidelberg.

Abstract
This paper describes the 5dpo team. The paper will be divided into three main sections, corresponding to three main blocks: the Global Level, the Local Level and the Interface Level. These Levels, their subsystems and some implementation details will be described next.

Abstract
Video segmentation is one of the most important parts of a vision system which allows partitioning each frame into homogeneous regions that share a common property. This work proposes a new methodology that aggregates three different techniques: background subtraction, region growing and a pseudo Fuzzy colour model to define colour subspaces that characterize each class. In addition, the pseudo Fuzzy colour model allows a given colour to belong to more than one class and enables the expansion ofthe classes through a dynamic model based on belonging and persistence information. In case of shared colours among classes, regional features are searched in order to determine the object's class. Tests with test and real videos of sports footages show promising results.