A reliable yet economical unmanned surface vehicle (USV) has been developed for the bathymetric surveying of lakes. The system combines an autonomous navigation framework, environmental sensors, and a multibeam echosounder to collect submerged topography, temperature, and wind speed and monitor the vehicle’s status during prescribed path-planning missions. The main objective of this research is to provide a methodological framework to build an autonomous boat with independent decision-making, efficient control, and long-range navigation capabilities. Integration of sensors with navigation control enabled the automatization of position, orientation, and velocity. A solar power integration was also tested to control the duration of the autonomous missions. The results of the solar power compared favorably with those of the standard LiPO battery system. Extended and autonomous missions were achieved with the developed platform, which can also evaluate the danger level, weather circumstances, and energy consumption through real-time data analysis. With all the incorporated sensors and controls, this USV can make self-governing decisions and improve its safety. A technical evaluation of the proposed vehicle was conducted as a measurable metric of the reliability and robustness of the prototype. Overall, a reliable, economic, and self-powered autonomous system has been designed and built to retrieve bathymetric surveys as a first step to developing intelligent reconnaissance systems that combine field robotics with machine learning to make decisions and adapt to unknown environments.