The Autonomous Systems and Controls Laboratory (ASCL), directed by Dan Stilwell, is developing water-based autonomous vehicles that can operate in platoons for monitoring lakes, rivers, and coastal waters. ASCL projects include developing mobile, robotic biochemical sensors for lakes and rivers, as well as miniature underwater robots to map Chesapeake Bay coastal waters for environmental studies and help develop search, survey, and tracking methods for the U.S. Navy.
The research challenges involve developing the miniature vehicles and sensors with their control and guidance algorithms; and control and estimation strategies for cooperating autonomous platoons where there is limited communication bandwidth.
Bradley Fellow Jamie Riggins is working to develop and construct an obstacle map that identifies an obstacle-free path for the group’s autonomous boat, or ASV (autonomous surface vehicle). When operating in unknown waters, or in changing environments, the ASV will need to detect obstacles quickly and accurately solely via imaging instruments.
The ASV will acquire a sequence of images, detect and track the obstacles in the images using image processing techniques, and use navigation sensors — including position and altitude — to calculate and map the location of the obstacles. “My work centers around the last part,” she explained. “I assume that the obstacles have already been marked on the images, and then I use those processed images, along with navigation information, to estimate, via a Kalman filter, the location of the obstacles.
Xiaojin Gong and Chris Wyatt from the BioImaging Laboratory are helping with the vision algorithms.