ABSTRACT The rising levels of water pollution worldwide, particularly in urban areas due to industrial advancements, have created an urgent need for sustainable and intelligent surface water cleaning solutions. Robotic systems have emerged as one of the promising approaches to tackle floating debris and other contaminants that affect aquatic ecosystems. This review critically examines the recent advancements in surface water cleaning robots, focusing on their structural designs, operational principles, autonomy levels, and energy efficiency. Particular emphasis is placed on the integration of guidance, navigation, and control (GNC) systems that enable semi‐autonomous and fully autonomous functionality. Existing robotic platforms vary widely in their mechanical setups and cleaning mechanisms, ranging from simple net‐based collectors to more advanced systems equipped with visual sensors and embedded control logic. However, a majority of these systems still depend on limited sensing and require periodic human intervention. The lack of advanced imaging technologies for debris detection, real‐time classification, obstacle detection and navigation restrict their autonomous potential. In addition to technical comparisons, the paper highlights the limitations and research challenges, including power management, visual processing capabilities, and adaptive path planning. The need for more intelligent, low‐power, and modular systems is emphasized, particularly those capable of handling diverse aquatic environments with minimal supervision. By consolidating current knowledge and identifying performance gaps, this review aims to guide future research efforts in the development of efficient, scalable, and environmentally sustainable robotic systems for surface water cleaning. These advancements are essential in promoting long‐term solution for water pollution, water resource management, and supporting efforts to maintain cleaner aquatic ecosystems.
Kumar et al. (Wed,) studied this question.