Cutting-Edge Research On A Comprehensive Development Approach In Robotics Manufacturing

This product signifies a notable breakthrough in the R&D Robotics sector in Vietnam. Developed by our in-house team, this innovative research embodies a comprehensive development approach.

The PowerGate Research team introduces the use of ultra-wideband impulse (UWB) radar for material classification. We utilized a single input-single output (SISO) radar operating at a center frequency of 7.25-GHz. To assess its capabilities, we tested it on eight different materials and objects, including books, notes, copper, aluminum, plastic, CDs, and cups.
Our methodology involved creating a deep convolutional neural network model trained directly on the raw UWB radar waveform signal. The results indicate that the SISO UWB radar achieved outstanding classification performance, surpassing a 90% average accuracy. This outperformed traditional machine learning models like support vector machines and Gaussian Naïve Bayes.

The potential applications of this approach are diverse, spanning from object recognition in manufacturing quality control to hidden object detection and material property analysis in various real-world scenarios.