tacterion, Germany
Thanks to a fusion system of embedded sensors and the implementation of Machine Learning algorithms, the exoskeleton (Agade) detects when the operator is carrying out manual picking operations which require support. It then automatically adjusts the assistance provided to the user.
The demo represents the functionality of the sensors in recognizing when to activate the exoskeleton to offer support to the user. It consist of three parts:
- The smart wireless armband that is used in the exoskeleton, integrated with plyon®’s multi-taxel of 7 active sensing areas, which process inputs from the muscles’ contraction and expansion. It also incorporates the seamlessly integrated force concentrator.
- Electronics flashed with Agade‘s Machine Learning model to read out the sensor‘s data output Screen for data visualisation: activation of different arm muscles
Purpose / Benefits
- Provide muscular assistance for workers during manual handling and picking tasks
- Show how the sensors can recognize which muscles are activated during which action and how this output can be used with a Machine Learning model to improve ergonomics, reduce stress on the worker’s shoulders and improve occupational safety
- It also highlights plyon®’s True Zero feature, which empowers the sensors to not show any signal when bended/wrapped around the arm, until physically actuated
Organic & Printed Components
- Printed sensor
Target Group
- Logistics
- Manufacturing
- Retailing