Karlsruhe Institute of Technology

Assembly Line

Deep Learning Boosts Robotic Picking Flexibility

Date:

Topics: robotics, federated learning

Organizations: Festo, Karlsruhe Institute of Technology, DarwinAI

Gripping and manipulating items of diverse shapes and sizes has long been one of the biggest challenges facing industrial robotics. The difficulty is perhaps best summed up by the Polanyi Paradox, which states that we “know more than we can tell.” In essence, while it may be easy to teach machines to exhibit a high level of performance on tasks that require abstract reasoning such as running computations, it is substantially harder to grant them the sensory-motor skills of even a small child in all but the most standardized and predictable environments.

Read more at Automation World