As one of the important means for human beings to understand and develop the ocean, the application of underwater robots in marine science and engineering has attracted more and more attention. Underwater robots are divided into two categories, one is remotely operated underwater vehicle (ROV) and the other is autonomous underwater vehicle (AUV). Autonomous submersibles do not carry cables. Its energy is installed on the robot. Its task execution process is controlled by computer. Complete the task independently according to the robot program. Because there is no cable constraint, further analysis data can be collected after returning. AUV has the characteristics of autonomous navigation and large-scale observation. This paper presents a method based on convolution neural network, which realizes the effective perception and recognition of underwater environment. Through the ROS operating system, we integrate the control and environmental perception of the underwater robot, and design an underwater robot that can avoid obstacles and recognize autonomously.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.