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What is Robotic Grippers about?
This paper presents a tactile sensing system for robotic grippers that classifies the hardness of objects in real-time using resource-constrained devices. It employs efficient pre-processing techniques and machine learning algorithms, achieving over 98% accuracy with convolutional neural networks while maintaining low memory usage and energy consumption. The study demonstrates the first embedded implementation of a complete data processing pipeline for hardness classification on a robot, addressing both com
- Author
- christian.gianoglio
- Language
- EN