Federico Furlan

Centro de Investigación en Computación

Computer Science, PhD•  January 2017 - Present

The research focuses on detecting obstacles in unstructured environments where all objects have similar color and texture characteristics. I proposed segmentation and detection techniques based on convolutional neural networks (Deep Learning) using mars-like images in Python. Additionally, I am developing a virtual environment in ROS to test the object detection or object segmentation algorithms as part of an autonomous navigation system using a Rover model.