Design and Realization of a Novel Robotic Manta Ray for Sea Cucumber Recognition, Location, and Approach
Source abstract
Abstract
Sea cucumber manual monitoring and fishing present various issues, including high expense and high risk. Meanwhile, compared to underwater bionic robots, employing autonomous underwater robots for sea cucumber monitoring and capture also has drawbacks, including low propulsion efficiency and significant noise. Therefore, this paper is concerned with the design of a robotic manta ray for sea cucumber recognition, localization, and approach. First, the developed robotic manta ray prototype and the system framework applied to real-time target search are elaborated. Second, by improved YOLOv5 object detection and binocular stereo-matching algorithms, precise recognition and localization of sea cucumbers are achieved. Thirdly, the motion controller is proposed for autonomous 3D monitoring tasks such as depth control, direction control, and target approach motion. Finally, the capabilities of the robot are validated through a series of measurements. Experimental results demonstrate that the improved YOLOv5 object detection algorithm achieves detection accuracies (mAP@0.5) of 88.4% and 94.5% on the URPC public dataset and self-collected dataset, respectively, effectively recognizing and localizing sea cucumbers. Control experiments were conducted, validating the effectiveness of the robotic manta ray’s motion toward sea cucumbers. These results highlight the robot’s capabilities in visual perception, target localization, and approach and lay the foundation to explore a novel solution for intelligent monitoring and harvesting in the aquaculture industry.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Water Quality Monitoring Technologies · Underwater Vehicles and Communication Systems · Coral and Marine Ecosystems Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animals and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing 100083, China
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Shandong Labor Vocational and Technical College, Jinan 250022, China
Funding
Chinese Universities Scientific Fund · National Natural Science Foundation of China
References (46)
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