# Simple Ultrasonic-Based Localization System for Mobile Robots
## 1 Introduction  
For several years now, we have been witnessing a significant increase in interest in the implementation of mobile robots indoors, both in buildings and warehouses [1]. This trend is driven by the need for more efficient management and automation of various tasks in industry and, not least, in households. One of the key challenges in the context of the movement of mobile robots in enclosed spaces is their ability to accurately determine their position in the operational space, which is a fundamental prerequisite for safe and effective navigation. Precise and reliable robot localization is essential for their ability to perform tasks reliably. Ineffective localization can lead to collisions, inefficient movement, or even failure to complete tasks [2; 3; 4; 5]. New technological approaches, such as combining different types of sensors, developing new algorithms, and utilizing artificial intelligence, have the potential to significantly improve the localization capabilities of mobile robots and take their performance and efficiency to a new level [6]. Currently, indoor localization is achieved using sensors and sensor systems placed on the robot itself [7]. These include ultrasonic sensors, infrared sensors, laser sensors, and lidars, as well as cameras (depth vision and stereo vision). Alternatively, less precise methods involve using Bluetooth or Wi-Fi signals. By combining odometry with the mentioned methods of determining position, a relatively robust and accurate localization system can be achieved indoors. Perhaps the most accurate positioning is achieved using laser lidars and subsequently utilizing Simultaneous Localization and Mapping (SLAM). However, there are limitations, such as when glass is used as walls in the environment. Therefore, it is sometimes appropriate to combine or use a localization system based on a similar principle to the well-known GPS (Global Positioning System) or GLONASS (Global Navigation Satellite Systems) [8; 9; 10]. Localization, the process of determining the position of an object or entity within a given space, is a fundamental aspect of various technological applications, including robotics, navigation systems, and augmented reality. Over the years, numerous localization methods have been developed, each with its own set of advantages and disadvantages. Existing methods range from traditional techniques such as Global Positioning System (GPS) and Wi-Fi-based localization to more sophisticated approaches like computer vision and sensor fusion. In addition to these, other methods such as Bluetooth Low-Energy (BLE), Ultra-Wideband (UWB), High-Frequency signals (HF), indoor localization infrastructure--radio-based (RF) and ultrasound-based (US), BTS (Base Transceiver Station), and Simultaneous Localization and Mapping (SLAM) have been introduced [11; 12; 13; 14]. Existing Localization Methods:  
The Global Positioning System (GPS) is renowned for its worldwide coverage, offering high accuracy in pinpointing locations in outdoor settings. Its satellite-based technology ensures a reliable measure of location with a considerable degree of precision. However, the urban landscape, characterized by high-rise buildings and narrow streets, often referred to as 'urban canyons', can significantly interfere with the signal. Similarly, GPS's utility is markedly reduced in indoor environments due to the inability of the satellite signal to penetrate solid structures effectively. Wi-Fi-based localization emerges as a robust alternative in indoor settings where GPS falls short. This method leverages the ubiquitous presence of Wi-Fi networks, providing cost-effective and reasonably accurate location data. The primary advantage lies in its ability to utilize existing infrastructure without the need for additional hardware. Nevertheless, this technique is not without its limitations. High levels of signal interference and diminished accuracy in areas densely populated with Wi-Fi networks can pose challenges.