I. Introduction
Water is the most important resource that exists, without it, life in all its forms would be impossible to develop. In addition to the fact that all industrial and environmental processes depend on it. Water is a fundamental pillar for the planet, not only because of its importance for life, but also because it influences social, economic and technological development [1]. In Honduras, despite its importance, little research is being developed to monitor marine life, with exceptions such as a robot for monitoring coral reefs [2] and an algorithm for detecting marine species [3]. This makes it necessary to implement intelligent systems that measure water quality parameters. In order to prevent the error in accuracy involved in collecting physical samples to take to a laboratory, stations have been developed with an integrated sensor system to measure physical and chemical parameters of the water in real time. However, this brings with it a number of problems, including the need to implement several stations to monitor water quality in a large body of water. This solution may work perfectly well, but it entails a very high investment and is of little use if the source of possible contamination is unknown. As a result, more and more robotic solutions are being applied for environmental monitoring, including aquatic surface robots, which can be classified as unmanned surface vehicles (USVs) or autonomous surface vehicles (ASVs) [4]. The main difference being that the USV is teleoperated and the ASV moves autonomously. Aquatic surface robots surface water robots are usually classified according to their hull type, propulsion system and energy system [5]. This paper describes the design and development of a single-hull, differential-thrust driven and solar-powered robot capable of moving autonomously through mission planning and acquiring water quality information through sensors of pH, total dissolved solids (TDS) and temperature. Facilitating, this way, the remote and inexpensive data collection, as well as the identification of previously unknown sources of contamination in freshwater bodies.