About this event
This is a 30-minute webinar with approx. 10 mins available for Q&A afterwards.
3D machine vision systems are used extensively across a multitude of industries including manufacturing and logistics. Consistently reliable identification and picking of objects are absolutely necessary. But it doesn't always work out that way, and missed picks and even robot stalls can occur. A common cause is a lack of 'trueness' in the 3D vision system.
Accuracy, precision, and trueness are critical factors in 3D machine vision together form the quality of the camera's perception of reality. Zivid 3D color cameras are designed to deliver astonishing levels of trueness. But there is still confusion around these topics.
So we will take a deeper dive and explore what these things are, how they occur, and how we measure them. We will look into the best techniques used to get 'true-to-reality' images for robots and machines to work with and show why Zivid 3D color cameras excel at 'trueness'.
Topics we will cover:
Øyvind is the VP of Product at Zivid. He drives the product vision and execution for our exceptional 3D color cameras. Outside of work Øyvind's loves anything that is a serious challenge and can usually be found climbing something.
After graduation, Nicolò Boscolo started working in machine vision and 5 years ago was promoted to product manager for all the bin-picking related applications, here at IT+Robotics. Over the last 5 years, he has been working closely with companies and robot integrators worldwide in order to help them grow and master the bin-picking technology.
Zivid simply makes camera systems that set the bar in color 3D machine vision systems. We give robots human-like vision.
Robots that can see more, can do more.
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