An implementation of landmark-based position estimation function as an autonomous and distributed system for a mobile robot

We developed APCS (autonomous position correction system) that can autonomously cancel the error of the estimated robot position from odometry by detecting flat walls using ultrasonic sensing. When it detects flat walls in the environment, this system corrects the estimated position using maximum likelihood estimation (MLE). The feature of this system is that it can correct the position not being concerned with the behavior of the robot because the system autonomously decides the trigger of the position correction. We show the algorithm and implementation of APCS, and some experimental results to confirm feasibility of the system in a disordered environment