Mobile Robot Localisation and Navigation Using LEGO NXT and Ultrasonic Sensor

TL;DR

This paper presents an affordable indoor robot localisation and navigation system using LEGO NXT and ultrasonic sensors, employing particle filtering and sampling-based path planning to achieve high accuracy.

Contribution

It introduces a cost-effective localisation and navigation approach using ultrasonic sensors and particle filters on LEGO NXT robots, with proven simulation and real-world results.

Findings

Achieved 1-3 cm localisation accuracy in simulations.

Effective ultrasonic data processing method developed.

Real-world experiments confirmed system effectiveness.

Abstract

Mobile robots are becoming increasingly important both for individuals and industries. Mobile robotic technology is not only utilised by experts in this field but is also very popular among amateurs. However, implementing a mobile robot to perform tasks autonomously can be expensive because of the need for various types of sensors and the high price of robot platforms. Hence, in this paper we present a mobile robot localisation and navigation system which uses a LEGO ultrasonic sensor in an indoor map based on the LEGO MINDSTORM NXT. This provides an affordable and ready-to-use option for most robot fans. In this paper, an effective method is proposed to extract useful information from the distorted readings collected by the ultrasonic sensor. Then, the particle filter is used to localise the robot. After robot's position is estimated, a sampling-based path planning method is proposed for the robot navigation. This method reduces the robot accumulative motion error by minimising robot turning times and covering distances. The robot localisation and navigation algorithms are implemented in MATLAB. Simulation results show an average accuracy between 1 and 3 cm for three different indoor map locations. Furthermore, experiments performed in a real setup show the effectiveness of the proposed methods.