Abstract
A real-time map-building system is proposed for an autonomous underwater vehicle (AUV) to build a map of an unknown underwater environment. The system, using the AUV's onboard sensor information, includes a neurodynamics model proposed for complete coverage path planning and an evidence theoretic method proposed for map building. The complete coverage of the environment guarantees that the AUV can acquire adequate environment information. The evidence theory is used to handle the noise and uncertainty of the sensor data. The AUV dynamically plans its path with obstacle avoidance through the landscape of neural activity. Concurrently, real-time sensor data are “fused” into a two-dimensional (2D) occupancy grid map of the environment using evidence inference rule based on the Dempster-Shafer theory. Simulation results show a good quality of map-building capabilities and path-planning behaviors of the AUV.
Highlights
Autonomous underwater vehicle (AUV) is an unmanned underwater robot widely used in underwater environments to accomplish underwater missions, such as pipeline tracking, large-scale underwater exploration, and seafloor search for wrecks
This paper focuses on building a map of an unknown underwater environment for an AUV, using the AUV’s on board sensor information only
When the AUV moves to the location (1, 4), an obstacle is detected by the sensor
Summary
Autonomous underwater vehicle (AUV) is an unmanned underwater robot widely used in underwater environments to accomplish underwater missions, such as pipeline tracking, large-scale underwater exploration, and seafloor search for wrecks. Autonomous robot requires map information from its onboard sensors to plan its path, especially in an unknown environment. Luo and Yang [10] used onboard sensor information for concurrent map building and complete coverage navigation of cleaning robot in unknown indoor environments. This paper focuses on building a map of an unknown underwater environment for an AUV, using the AUV’s on board sensor information only. A complete coverage path planning of AUV by using a neurodynamics model is proposed for the real-time map-building system.
Sign-in/Register to view highlights & summary 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 callMore From: International Journal of Distributed Sensor Networks
Disclaimer: 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.
