Human-Robot Collaboration in the Smart Factory through Federated Learning
As a manufacturer of cobots, you want to enable true human-robot collaboration (HRC) in a shared workspace. To do this, you want to learn from different production processes in practice. However, industrial robots are mainly used in sensitive production environments, where no process data can be shared.
Learn how one cobot manufacturer enables safe human-robot collaboration without learning about its customers.
The Federated Learning Case Study for Machine Builders in Robotics
True human-robot collaboration requires that your cobots learn and apply customized safety strategies to avoid collisions. In simulation environments, it is difficult to expose the cobots to a variety of different situations that can occur in practice. This is because it is the rare events or unpredictable motion sequences that require machine learning models that reflect a variety of different situations from production. Katulu Federated Learning can do just that without sensitive data leaving your customers' production environments.
Your Key Benefits
- Use real-world process data for your human-robot collaboration training
- Group robots by tools based on their hazard potential to enable adapted behavior in MRC
- Provide your customers with continuous tailored improvements
- Benefit from continuously updated knowledge from the field
- Prevent inferences about production processes through anonymized machine learning
- Your robots learn from each other - without learning about each other
Read our case study to learn more about how Federated Learning can benefit your business and strengthen your competitive position.
Learn how a robotics manufacturer, Katulu, uses Federated Learning to optimize human-robot collaboration with real-world process data without sharing sensitive production data.
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