In this article, the development of a bat-ray-inspired underwater vehicle is presented; although the propulsion of the vehicle is based on traditional thrusters, the shape of the ray’s fins was used as a model to design the body of the vehicle; this architecture allows the independent control of the forward velocity and the full attitude of the vehicle using only two thrusters and two articulated fins. The compact design of the robot, along with the high dexterity of the architecture, allows the vehicle to submerge and emerge vertically as well as navigate horizontally. The mathematical model of the proposed vehicle, including dynamics and propulsion system, is presented and validated using numerical simulations. Finally, experimental tests are presented to demonstrate the capabilities of the proposed design.

The localization in mobile robotics is essential for carrying out autonomous tasks. For this reason, different algorithms have been developed to estimate the robot's pose, either relatively or absolutely. One of the best known is Wheel-based Odometry, which is easy to implement but the error tends to increase with respect to time producing an unreliable estimation. In contrast, absolute localization algorithms such as Generalized Geometric Triangulation (GGT) offer higher accuracy, although their implementation may require more advanced measurement systems, and pose estimation can be slow. This work compares these two algorithms and shows what happens with the pose estimation when used for period of time. The presented results were obtained in a real testing area equipped with a Turtlebot3 model burger robot.

Marine robotics has become central to contemporary ocean exploration and conservation, providing unprecedented access, precision, and continuity in the observation of marine environments. This chapter examines the capabilities and emerging roles of autonomous underwater vehicles, remotely operated systems, and hybrid robotic platforms in mapping seafloor structures, monitoring ecological dynamics, and supporting restoration initiatives in sensitive habitats. It evaluates recent advances in perception, navigation, and machine-driven decision-making that enable robots to operate safely and adaptively in complex, uncertain, and data-scarce marine settings. Furthermore, the chapter discusses the integration of robotics with oceanographic sensors, artificial intelligence, and real-time communication infrastructures to enhance environmental intelligence. Ethical considerations, operational challenges, and future research pathways are also addressed to guide the responsible deployment of robotic technologies for long-term marine sustainability.