Title

Labeling Paths with Convolutional Neural Networks

Author(s) Information

Sean Wallace, California Polytechnic State University, San Luis ObispoFollow
Kyle Wuerch, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Engineering

Department - Author 1

Computer Engineering Department

Degree Name - Author 1

BS in Computer Engineering

Date

6-2019

Primary Advisor

John Seng

Abstract/Summary

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy of over 95%.

URL: https://digitalcommons.calpoly.edu/cpesp/315