Better Eyes; Better Robot Outcomes
With better eyes, we get better robot outcomes which lead to more trust in our automation systems
Guest post by Raman Sharma, VP of Sales Americas.
Customer visits provide an excellent learning possibility. Recently I met a company that makes robotic automation systems for a variety of industrial automation applications, including palletization and depalletization for the food and beverage industry. The primary challenge facing them was to automate the task of beverage palletization. I noted down some of their difficulties;
- Identify cases, with and without labels or specific markings
- Avoid tricks that cardboard bulges, overzealous flaps, and damaged corners play on less sophisticated robot vision systems
- Reliably describe what to look for when carton sizes regularly change to marketing needs
- Assure that beverage cases, once shrink wrapped, don't have "tails" that get snagged in machinery
The common denominator? The smart people in the R&D department at the customer realized all their automation problems were related to machine vision systems.
Everything is a vision situation. A well-designed vision system can alleviate many, if not all, of the problems outlined by the customer. An ideal machine vision solution allows;
- SKUs to be verified by sight independent of markings and labels
- Mitigates against object orientation issues
- Deals with creative marketing departments that need to modify packaging
However, the customer had not yet found a solution that checked off everything on their list of requirements:
- Human-like 3D imaging
- High acquisition and data processing speed
- Software APIs and tools
- Ease of use
- Robustness for use on factory floors
Enter the award-winning Zivid One, the world’s most accurate real-time 3D color camera.
With specifications illustrated above, Zivid One can be the eyes for industrial automation systems, ensure more robust performance and enable automation of tasks that were previously difficult or impossible to automate.
It's safe to say that Zivid One checks all the boxes. With better eyes, we get better robot outcomes which lead to more trust in our automation systems.