Autonomous Driving Segway Robots

Abstract

In this thesis, an autonomous driving robot has been proposed and built based on a two-wheel Segway self-balancing scooter. Sensors including LiDAR, camera, encoder, and IMU were implemented together with digital servos as actuators. The robot was tested simultaneously with the functionality features including obstacle avoidance based on fuzzy logic and 2D grid map, data fusion based on co-calibration, 2D simultaneously localization and mapping (SLAM) and path planning under different scenarios both indoor and outdoor. As a result, the robot initially has the ability of self-exploration with avoiding obstacles and constructing 2D grid map simultaneously. A simulation of the robot with same functionalities except data fusion has also been tested and performed based on robot operating system (ROS) and Gazebo as the simple comparison of the robot in real world.