Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle

Robot machine capture protein seafood like sea cucumber and seashell is expected to play a great role in food economy improvement and divers protection. In order to realize robot capture, a sea organism absorptive type remotely operated vehicle (ROV) has been designed with the pilot operation and visionbased autonomous capture modes. A novel region-based fully convolutional network with deformable convolutional networks has been developed to realize organism target recognition. The comparisons in offline experiments have verified its advantages. In order to realize organism target following and capture control, a novel learning-based type-II fuzzy controller has been developed. Through online fuzzy rule optimization and learning, the controller can realize organism target following and capture control under image coordinate without vehicle horizontal velocity or position information in the complicated submarine environment. Field trials have been made in the Zhangzidao Island of China with the designed absorptive type ROV. The trials manifest that the designed absorptive type ROV can realize online organism target recognition, following and capture in the real submarine environment.