We are conducting core research on developing a multi-legged autonomous walking robot (Crabster) capable of navigating underwater. Our studies focus on critical technologies such as force control for autonomous walking on the seabed, SLAM, and perception technologies. To support this, we are conducting foundational research on autonomous walking and force control using the underwater-capable Unitree B1 robot. These core technologies will be applied to enhance the performance of seabed-walking robots.

We developed an autonomous cleaning system using a multi-degree-of-freedom manipulator to recognize and clean areas affected by biofouling in niche regions of ship hulls. To accurately identify and assess various shaped niche areas, We developed an underwater laser-camera system. We then used Iterative Closest Point (ICP) and full coverage path planning algorithms to generate the optimal cleaning path. Subsequently, We controlled a 6-DOF hydraulic manipulator along these paths, taking into account potential collisions between the manipulator and the target area. This system was validated both on land and underwater, successfully identifying the target areas with precision using the laser-camera system and effectively removing biofouling organism imitations from the surfaces.  Video Clip link

Development of vision-based underwater object recognition and tracking technology using dual-arm robot. We aim to develop a technology to improve the recognition / cognition performance of marine environments and objects by installing camera sensors on two-armed robots and using them for image recognition and tracking of dynamic objects underwater. Based on these technologies, we plan to develop autonomous underwater work technology using two-armed marine robots.

To prevent potential accidents during underwater remote operations and to ensure consistent performance, we proposed a Cyber-Physical Operation System (CPOS). This technology analyzes real-time physical models based on the dynamic and inverse dynamic models of the robot and implements the information obtained from the sensors attached to the robot and the surrounding environment into a digital environment, ensuring robust performance even in varying working conditions. Additionally, to effectively convey the robot's operational environment and status to the operator, we established a Human-in-the-Loop (HILS) environment. This setup allows the operator to control the system as if they were physically performing the tasks. We applied this HILS environment to an underwater work vehicle (referred to as a rover), which is a typical remote-controlled underwater robot, and designed a cognitive/control framework for it. The proposed system was actually designed, developed, and applied to underwater robot control (On going). 

Researching autonomous technology, navigation, and control for autonomous underwater vehicles. The underwater environment is difficult to use land-based technologies due to the influence of the medium. We conduct research to develop and demonstrate autonomous system algorithms suitable for underwater environments and underwater robots. Video Clip link