Abstract
This paper describes a situation assessment system for an autonomous underwater vehicle (AUV). This system is a result of research on knowledge-based guidance systems applied to AUVs, which is currently taking place at the Marine system Engineering Laboratory, University of New Hampshire. This paper gives the reader some background on the project, an introduction to the MSEL KBS architecture, and a description of how the situation assessment system is implemented. In a dynamic world with a complex mission, a mobile robot needs the ability to analyze its environment and its situation. We call this situation assessment. Since unplanned situations will most likely occur, the robot will need some ability to perform qualitative reasoning on its situation, before it modifies its original plan. This qualitative reasoning implies a system capable of building and maintaining a model of the vehicle's environment and itself. It also involves use of data from several different sources (sensor fusion) and combining these data into more abstract terms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
