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Machines Building Trust

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JAMES SCHLETT, EDITOR, [email protected]

James SchlettPeople around the world are not ready yet to completely trust machines, at least when it comes to driving.

That is what the luxury automaker Volvo Cars Corp. found after conducting an international survey with 10,000 respondents — 92 percent of whom said an autonomous vehicle should include features that allow human drivers to take control of it at any given time. This survey echoed a similar distrust uncovered by a 2014 survey of 2,000 drivers by, which found 61 percent of respondents did not believe a computer could replicate the split-second decisions that humans make on the road.

While people may be apprehensive about letting a machine drive them to work, they are more open to working beside one, even if it is equipped with intimidating features such as lasers or grabbers. As illustrated by this month’s Industrial Photonics cover story, “Collision Avoidance Moves into More Dynamic Automation Environments,” by Tim Dykstra at Concept Systems Inc. (read article), machine-human interactions are only becoming more common on factory floors. And just as autonomous vehicle collision avoidance systems are relying on lidar sensors to prevent one car from hitting another or pedestrians, similar technology is being used to prevent manufacturing robots from injuring humans.

Other feature articles you will not want to miss in this issue include:

• “Know Your Needs for Best Machine Vision Camera Selection,” by Glen Ahearn at Teledyne Dalsa Inc. (read article).

• “An Introduction to Laser Process Qualification,” by Jochen Deile and Frank Gaebler at Coherent Inc. (read article).

• “Packaging Automation Overcomes Optoelectronic Component Variety,” by Guenter Hummelt at Nanosystec GmbH (read article).

If you are interested in contributing a technical article for Industrial Photonics that will reach our highly knowledgeable global audience — and that will also be featured prominently at conferences and trade fairs around the world — please send an informal, approximately 100-word abstract to [email protected] for consideration. I’ll then review the abstract and get back to you on possible placement.

Enjoy the issue!
Mar 2016
machine vision
Interpretation of an image of an object or scene through the use of optical noncontact sensing mechanisms for the purpose of obtaining information and/or controlling machines or processes.
industrialmachine visioncollision avoidanceVolvo CarsJames SchlettConcept SystemsTim DykstraEditorial

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