Integration of Look-Ahead Control and Multi-Sensor Fusion Capability for an Autonomous Mobile Robot under Outdoor Environment

Abstract

When building autonomous mobile robots, the challenge has often been to create a system capable of functioning as intended to even if some components fail. This research aims to approach the problem by fusing multiple sensor data using an extended Kalman filter and probabilistic occupancy mapping. A nonholonomic feedback controller controls a mobile robot which uses the pose obtained from the extended Kalman filter as a reference frame for the sensors. We use ROS framework as a base to implement this on our system.