Compensation of electrical current drift in human-robot collision
1Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USA.
The International Journal, Advanced Manufacturing Technology
|June 13, 2024
Summary
This study developed a neural network controller to compensate for electrical current sensor drift in collaborative robots. This improves safety by reducing impact forces during human-robot collisions.
Area of Science:
- Robotics
- Control Systems
- Sensor Technology
Background:
- Collaborative robots are increasingly used in manufacturing.
- Electrical current sensors in robots can drift, causing inaccurate torque and force readings.
- Sensor drift poses a safety risk during human-robot interactions.
Purpose of the Study:
- To develop a method for compensating electrical current sensor drift in industrial robot arms.
- To reduce impact forces during human-robot collisions.
- To quantify the effect of sensor drift on collision dynamics.
Main Methods:
- A neural network-based controller was designed to manage robot velocity.
- An experimental setup involved robot joint collisions with a biofidelic forearm model.
- Soft force sensors measured deformation and contact forces during collisions.
Main Results:
- The proposed method effectively compensated for electrical current sensor drift.
- Reduced contact forces were observed during human-robot collision simulations.
- The study quantified sensor drift's impact on collision behavior.
Conclusions:
- A data-driven methodology for compensating electrical current sensor drift was presented.
- The neural network controller enhanced safety in human-robot collaborative systems.
- This research contributes to safer and more reliable robot operation.
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