Authors: Jin Z, Shao Y, So M
University affiliation: The Cooper Union for the Advancement of Science and Art
Department: Electrical Engineering
Abstract: Simultaneous localization and mapping (SLAM) has been an emerging research topic in the fields of robotics, autonomous driving, and unmanned aerial vehicles over the last 30 years. Unfortunately, SLAM research is generally inaccessible for student researchers due to expensive hardware and painful software setup. By introducing a loosely coupled, modular multi-sensor data fusion architecture, we present an autonomous driving research platform that can be adapted to computing platforms with various computational constraints and serve multiple applications and educational purposes. Our goal is to create an easily accessible SLAM module with cost-friendly hardware dependencies and minimal software setup for SLAM researchers, teachers, and learners.
Submitted by: Zhekai Jin
Major: Electrical Engineering
Degree being pursued: BS
Type of student: Senior