Indoor mobile robot localization using KNN

This paper describes the usage of sixteen piece 40 kHz ultrasonic sensors, known as Ultrasonic Sensor Bank (USB-16) mounted on a mobile robot platform. The Homogeneous Transformation Matrix (HTM) and trigonometric algorithm is utilized in this research as a wall mapping algorithm. The walls were designed with four types of basic shapes such as rectangle, triangle, curved and square, which are rarely tested by researchers in real time. Mapping and localization within real laboratory environment was also conducted. In this research, the USB-16 sensor bank transmitted ultrasonic signals in frequency waveform to the wall; the reflected signal was then filtered by a Nominal Wall Angle (NWA) algorithm to optimize the accuracy of the measured data. The purpose of this research is to determine the capability of USB-16 in not only providing an accurate map, but also its capability to recognize shapes and localization during mapping based on the size of walls. Next, NWA and KNN algorithm were applied in this experiment to study the accuracy of localization algorithm. This experiment had been carried out with two types of data sets, distance and coordinates. With the combination of these algorithms, the system can improve the accuracy of localization from 80% to 90% for basic wall shape and 78% for real laboratory environment. Basic Stamp, Basic Atom, LabVIEW and MATLAB software were fully utilized in the Self Localization and Mapping problem.