Environment perception, localization and navigation are critical for autonomous driving. Their solutions in indoor environment are different from that for outdoor driving. In this project, we will use WiFi based indoor localization to provide rough location information. SLAM (simultaneous localization and mapping) will then be utilized to provide accurate localization and mapping for navigation purpose. The objective of this project is to build an autonomous driving robot that can work in indoor environment.
UROP1000 UROP1100 UROP2100 UROP3100 UROP4100
Students will work in one of the following areas
1. Improve the available WiFi indoor localization algorithm.
2. Investigate the integration of WiFi localization and SLAM algorithm.
3. Improve the user-machine interface
4. Machine learning algorithm to improve the WiFi indoor localization algorithm.
Applicant's Learning Objectives:
1. Understand key technologies for autonomous driving
2. Understand indoor localization algorithm
3. Understand machine learning and its application in this project