Unmanned Surface Vehicles (USVs) have emerged as key enablers of autonomous maritime operations, offering innovative solutions across multiple industries, including defense, oceanography, offshore energy, and logistics. This review examines the current state of operative USVs, analyzing their technological evolution, design characteristics, and applications. The study highlights trends in autonomy, propulsion, endurance, and communication technologies, providing insights based on market-ready platforms. While USVs present significant advantages in terms of efficiency and operational safety, challenges such as regulatory constraints, cybersecurity risks, and limitations in autonomous decision-making persist. This paper aims to update researchers, policymakers, and industry stakeholders on the technological advancements and emerging trends shaping the future of unmanned vehicles.

When considering a system composed of a group of robots, swarm robotics is an approach that can be used to coordinate this group. These swarms can be inspired or not by social insects or other animal societies (Trianni, 2008), where basic behaviors are usually used to compose complex tasks. These previously mentioned basic behaviors have been studied for a long time, with applications, for example, to flocks, herds, and schools (Reynolds, 1987) and multi-robot teams (T. Balch & Arkin, 1998). Here we introduce PySwarming, a tool that makes easy the coordination of swarms and serves as a centerpiece, organizing different methods developed in the swarm robotics field. Its flexibility (written in Python) and customizability (easily customized by users) encourage interaction and scientific progress in the research community.

This article presents a review of research on swarm behaviors that fall under the categories of behavior-based, physics-based, and rule-based approaches. The authors classify these approaches as straightforward distributed behaviors and argue that despite their differences, they share a common root and can be studied together. The article highlights the diverse range of applications that have been explored using these approaches, such as manipulators, mobile robots, flocks, and escape panic scenarios. The authors aim to provide a shared nomenclature standardization for these behaviors, allowing for better understanding and connection between the different models. This review contributes to the evolution of swarm intelligence research and offers insights into the potential of straightforward behaviors in various domains.