2D Indoor Simultaneous Localization and Mapping (SLAM) Navigation Robot

Final Year Project in Engineering at University of Glasgow Singapore (UGS) and Singapore Institute of Technology (SIT)

Student: Student: Lim Teng Jiao
Supervisor: Supervisor: Prof. Chee Kiat (Lawrence) Seow (UGS)

Project Description:
Simultaneous Localization and Mapping (SLAM) technology has gained momentum especially with the advent of autonomous vehicle, drones and robot that replace menial task such as delivery task. In indoor environment, there are robots that serves the customer in restaurant and boutique hotels. Nowadays even the vacuum cleaner is a robot. In order to navigate to the designated location, the robots need to sense making of the environment.
Traditionally, laser based sensor such as LIDAR will mount on the robot and the robot will apply SLAM algorithm to navigate to the designation. Recent years saw the introduction of Visual SLAM that includes camera as the sensor.
This project will research into Visual SLAM to allow better sense making of the environment especially dynamic objects such as human. The student will explore application of Machine learning such as RCNN to improve accuracy of the visual SLAM mapping.