Abstract: This article presents a strategy for identifying the source location of a chemical plume in near-shore oceanic environments where the plume is developed under the influence of turbulence, tides and waves. This strategy includes two modules: source declaration (or identification) and source verification embedded in a subsumption architecture. Algorithms for source identification are derived from the moth-inspired plume tracing strategies based on a chemical sensor. The in-water test missions, conducted in November 2002 at San Clemente Island (California, USA) in June 2003 in Duck (North Carolina, USA) and in October 2010 at Dalian Bay (China), successfully identified the source locations after autonomous underwater vehicles tracked the rhodamine dye plumes with a significant meander over 100 meters. The objective of the verification module is to verify the declared plume source using a visual sensor. Because images taken in near shore oceanic environments are very vague and colors in the images are not well-defined, we adopt a fuzzy color extractor to segment the color components and recognize the chemical plume and its source by measuring color similarity. The source verification module is tested by images taken during the CPT missions.
Keywords: insect-inspired robots; chemical plume tracing; autonomous underwater vehicle; odor source identification; fuzzy color segmentation
Export to BibTeX
MDPI and ACS Style
Tian, Y.; Kang, X.; Li, Y.; Li, W.; Zhang, A.; Yu, J.; Li, Y. Identifying Rhodamine Dye Plume Sources in Near-Shore Oceanic Environments by Integration of Chemical and Visual Sensors. Sensors 2013, 13, 3776-3798.
Tian Y, Kang X, Li Y, Li W, Zhang A, Yu J, Li Y. Identifying Rhodamine Dye Plume Sources in Near-Shore Oceanic Environments by Integration of Chemical and Visual Sensors. Sensors. 2013; 13(3):3776-3798.
Tian, Yu; Kang, Xiaodong; Li, Yunyi; Li, Wei; Zhang, Aiqun; Yu, Jiangchen; Li, Yiping. 2013. "Identifying Rhodamine Dye Plume Sources in Near-Shore Oceanic Environments by Integration of Chemical and Visual Sensors." Sensors 13, no. 3: 3776-3798.