Sensor fusion for differential encoder integrated with light intensity sensors and accelerometer

This paper proposed mainly fusions between encoders and light intensity sensors and between encoders and accelerometer for distance increment with Kalman filter to estimate robot´s position. A developed fusion algorithm between differential encoder system and light intensity sensor, and accelerometer is analyzed and experimental tested in square shape. Applying the Kalman filtering theory, we successfully fused differential encoders and external sensors to obtain improved position and heading angle estimation. Finally, the experimental result and simulation present the different trajectory generated by only differential encoders and differential encoders integrated with external sensors system.