Abstract: Shipborne rotorcraft UAVs, characterized by high maneuverability, vertical take-off and landing capabilities, and superior environmental adaptability, serve as critical platforms for conducting highly dynamic collaborative detection missions in complex maritime conditions. Motion planning technology is a key enabler for ensuring mission effectiveness. This paper first summarizes the key technologies involved, including dynamically constrained feasible trajectory modeling, complex maritime environment perception, and collaborative localization. It then systematically reviews and categorizes the state of the art in related research both domestically and internationally into four major categories: spatial geometric constraint-based path planning, space-time trajectory optimization under differential flatness constraints, learning-based maneuver decision-making, and multi-UAV collaborative motion planning. The maneuverability and real-time performance of these approaches are further analyzed and compared. Finally, in response to existing technical challenges, future development trends and research directions are proposed, including deep collaboration tailored to complex shipborne environments, LLM-enabled high-level decision-making, and end-to-end reactive maneuvering within an embodied intelligence framework. These efforts aim to provide technical references for the autonomous and intelligent development of future shipborne UAV swarms.