Persistent Ocean Monitoring with Underwater Gliders: Towards Accurate Reconstruction of Dynamic Ocean Processes
This paper proposes a path planning algorithm and a velocity control algorithm for underwater gliders to persistently monitor a patch of ocean. The algorithms address a pressing need among ocean scientists to collect high-value data for studying ocean events of scientific and environmental interest, such as the occurrence of harmful algal blooms. The path planner optimizes a cost function that blends two competing factors: it maximizes the information value of the path, while minimizing the deviation from the path due to ocean currents. The speed control algorithm then optimizes the speed along the planned path so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California over the course of several weeks. The results show significant improvements in data resolution and path reliability compared to a sampling path that is typically used in the region.
Ryan N. Smith Mac Schwager Stephen L. Smith Daniela Rus Gaurav S. Sukhatme
School of Engineering Systems at the Queensland University of Technology,Brisbane,QLD,4000 Australia GRASP Lab,University of Pennsylvania,Philadelphia,PA 19104,USA Distributed Robotics Lab,Computer Science and Artificial Intelligence Laboratory,Massachusetts Insti Robotic Embedded Systems Laboratory,Department of Computer Science,University of Southern California
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
1517-1524
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）