Koi Care Robots: A Framework and Practical Applications

This study proposes a robotic framework for intelligent koi pond management, aimed at enhancing the care and well-being of koi in controlled aquatic environments. The robotic platform is designed with multiple integrated subsystems, including a water filtration unit, real-time koi monitoring, water quality sensing and analysis, joystick-enabled man-ual operation, and automated navigation. The prototype integrates several sensing com-ponents, including a 9-axis inertial measurement unit (IMU), an underwater distance sensor, an underwater camera, and a 2D LiDAR system. The IMU supplies continuous feedback on orientation and dynamic stability, supporting precise navigation and control performance. The underwater distance sensor facilitates real-time detection of sub-merged obstructions to ensure safe underwater operation. Visual data acquired by the underwater camera are processed using deep learning–based classification algorithms for object recognition. Additionally, the 2D LiDAR sensor detects and maps above-water obstacles, supporting reliable navigation and environmental awareness. The robotic framework is implemented using ROS2, which manages system integration, communication, and control. The water purification subsystem consists of four pumps that intake pond water and channel it through an integrated filtration module. Real-time water quality evaluation is achieved through deep learning–based analysis and classification of underwater imagery. Furthermore, the system is integrated with an automated feeding machine that dispenses floating pellets using deep learning. In addition, the system inte-grates EC, pH, and dissolved oxygen (DO) sensors to continuously monitor key water quality parameters essential for koi health and aquaculture productivity via Bluetooth communication. The robot is powered by a solar energy system, enabling autonomous and sustainable operation. Experimental results demonstrate the robustness and reliability of the framework in real-world conditions.