渔业机器人的研发应用进展与展望OA

In response to the demand for safety,efficiency,and low-carbon operation and maintenance in modern fisheries,fishery robotic systems are gradually shifting from"single equipment replacing manual labor"to"sustainable engineering systems"in precision aquaculture,marine fishing,and resource monitoring applications.Their significance lies in automating and digitizing high-frequency operations such as inspection,feeding,cleaning,maintenance,and monitoring,thereby reducing personnel risks,improving operational consistency,and management accuracy in complex water areas.Based on this,the collaborative configuration of platform form and key subsystems has become the main thread for understanding the capability boundaries and application landing points of fishery robotic systems.Fishery robotic systems are mainly composed of five systems:platform and propulsion,energy and power,perception and sensing,navigation and control,decision-making and intelligence.They form complementary configurations around four types of operating environments:land-based covered workshops and shore-based process operations;underwater environments focused on close-range maintenance of cages and facilities;water surface environments responsible for navigation monitoring,feeding,and communication support;and aerial platforms for wide-area patrol and remote sensing evaluation.In this complementary pattern,the research focus has shifted from single-point functional improvement to a comprehensive balance between system-level collaboration and engineering constraints.Technological development is advancing towards multi-platform collaboration and data-driven applications,but there are still engineering constraints in terms of endurance,underwater sensing communication,and long-term reliability.For regular deployment,priority directions include platform modularization and interface standardization,collaborative communication under low bandwidth conditions,task level energy planning and replenishment system,as well as trusted AI and security constraint control for uncertainty,which need to be improved in coordination with operation and maintenance mechanisms and industry standards.