Applying low cost WiFi-based localization to in-campus autonomous vehicles

In this paper a new approach to provide low cost localization to autonomous vehicles is proposed. It is based on fingerprint WiFi localization improved by using Support Vector Regression to increase localization resolution without the need of increasing the number of positions to site-survey. Results shown that the proposed method can emerge as a powerful tool to provide localization at situations where the use of GPS is not suitable.