Published September 6, 2024
| Version v1
Journal article
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Using LSTM Recurrent Neural Networks to Predict the Trajectory of Human Hand Movement in the Working Area of a Collaborative Robot-Manipulator
Creators
- 1. Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine
- 2. Senior Developer Electronic Health Solution, Amman, Jordan
Description
The article examines the use of LSTM recurrent neural networks for predicting the trajectory of human hand movement in the working area of a collaborative robot-manipulator. The results demonstrate high prediction accuracy for slow movements, but reveal certain limitations for fast and complex trajectories. The proposed approach is aimed at improving the safety and efficiency of the joint work of humans and robots within the framework of the concept of Industry 5.0.
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17-32 Vladyslav Yevsieiev .pdf
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Additional details
References
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