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.
References
[1]
Belanger, J.H.; Willis, M.A. Biologically-Inspired Search Algorithms for Locating Unseen Odor Sources. Proceedings of the IEEE International Symposium on Intelligent Control (ISIC), Held Jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Gaithersburg, MD, USA, 14–17 September 1998; pp. 265–270.
[2]
Li, W.; Farrell, J.A.; Cardé, R.T. Tracking of fluid-advected chemical plumes: Strategies inspired by insect orientation to pheromone. Adapt. Behav. 2001, 9, 143–170.
[3]
Grasso, F.W.; Basil, J. How lobsters, crayfishes, and crabs locate sources of odor: Current perspectives and future directions. Curr. Opin. Neurobiol. 2002, 12, 721–727.
[4]
Minagawa, Y.; Myoren, Y.; Ishida, H. Crayfish Robot Employing Flow Induced by Waving to Locate a Chemical Source. Proceedings of Seventh International Conference on Machine Learning and Applications, San Diego, CA, USA, 11–13 December 2008; pp. 482–488.
[5]
Lochmatter, T.; Martinoli, A. Tracking odor plumes in a laminar wind field with bio-inspired algorithms. Spr. Tract. Adv. Rob. 2009, 54, 473–482.
[6]
Hayes, A.T.; Martinoli, A.; Goodman, R.M. Swarm robotic odor localization: Off-line optimization and validation with real robots. Robotica 2003, 21, 427–441.
[7]
Kang, X.D.; Li, W. Moth-inspired plume tracing via multiple autonomous vehicles under formation control. Adapt. Behav. 2012, 20, 131–142.
[8]
Meng, Q.H.; Yang, W.X.; Wang, Y.; Li, F.; Zeng, M. Adapting an ant colony metaphor for multi-robot chemical plume tracing. Sensors 2012, 12, 4737–4763.
[9]
Kowadlo, G.; Russell, R.A. Robot odor localization: A taxonomy and survey. Int. J. Rob. Res. 2008, 27, 869–894.
[10]
Cardé, R.T.; Willis, M.A. Navigational strategies used by insects to find distant, wind-borne sources of odor. J. Chem. Ecol. 2008, 34, 854–866.
[11]
Li, W.; Farrell, J.A.; Pang, S.; Arrieta, R.M. Moth-inspired chemical plume tracing on an autonomous underwater vehicle. IEEE Trans. Rob. 2006, 22, 292–307.
[12]
Li, W. Identifying an odour source in fluid-advected environments, algorithms abstracted from moth-inspired plume tracing strategies. Appl. Bionic. Biomech. 2010, 7, 3–17.
[13]
Farrell, J.A.; Pang, S.; Li, W. Chemical plume tracing via an autonomous underwater vehicle. IEEE J. Ocean Eng. 2005, 30, 428–442.
[14]
Kang, X.D.; Li, W.; Xu, H.L.; Feng, X.S.; Li, Y.P. Validation of An Odor Source Identification Algorithm via An Underwater Vehicle. Proceedings of Second International Conference on Intelligent System Design and Engineering Application, Sanya, China, 6–7 January 2012; pp. 740–743.
[15]
Brooks, R.A. A robust layered control system for a mobile robot. IEEE J. Rob. Autom. 1986, 2, 14–23.
[16]
Li, W.; Carter, D. Subsumption Architecture for Fluid-Advected Chemical Plume Tracing with Soft Obstacle Avoidance. Proceedings of Ocean 2006 Marine Technology and Ocean Science Conference, Boston, MA, USA, 18–21 September 2006; pp. 1–6.
[17]
Elkinton, J.S.; Schal, C.; Ono, T.; Cardé, R.T. Pheromone puff trajectory and upwind flight of male gypsy moths in a forest. Physiol. Entomol. 1987, 12, 399–406.
[18]
Kuenen, L.P.S.; Cardé, R.T. Strategies for recontacting a lost pheromone plume: Casting and upwind flight in the male gypsy moth. Physiol. Entomol. 1994, 19, 15–29.
[19]
Sabelis, M.W.; Schippers, P. Variable wind directions and anemotactic strategies of searching for an odour plume. Oecologia 1984, 63, 225–228.
[20]
Dusenbery, D.B. Optimal search direction for an animal flying or swimming in a wind or current. J. Chem. Ecol. 1989, 15, 2511–2519.
[21]
Farrell, J.A.; Pang, S.; Li, W. Plume mapping via hidden markov methods. IEEE Trans. Syst. Man Cybern. 2003, 33, 850–863.
[22]
Tang, S.M.; Guo, A.K. Choice behavior of drosophila facing contradictory visual cues. Science 2001, 294, 1543–1547.
[23]
Farrell, J.A.; Murlis, J.; Long, X.; Li, W.; Cardé, R.T. Filament Based atmospheric dispersion model to achieve short time scale structure of chemical plumes. Environ. Fluid Mech. 2002, 2, 143–169.
[24]
Sutton, J.; Li, W. Development of CPT_M3D for Multiple Chemical Plume Tracing and Source Identification. Proceedings of Seventh International Conference on Machine Learning and Applications, San Diego, CA, USA, 11–13 December 2008; pp. 470–475.
[25]
Li, W. Moth Plume-Tracing Derived Algorithm for Identifying Chemical Source in Near-Shore Ocean Environments. Proceedings of 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, 29October–2 November 2007; pp. 2162–2167.
[26]
Cheng, H.D.; Jiang, X.H.; Sun, Y; Wang, J.L. Color image segmentation: Advances and prospects. Patt. Recogn. 2001, 34, 2257–2281.
[27]
Fu, K.S.; Mui, J.K. A survey on image segmentation. Patt. Recogn. 1981, 13, 3–16.
[28]
Pal, S.K.; Pal, N.R. A review on image segmentation techniques. Patt. Recogn. 1993, 29, 1277–1294.
[29]
Li, W. An Iterative Fuzzy Segmentation Algorithm for Recognizing an Odor Source in Near Shore Ocean Environments. Proceedings of the International Symposium on Computational Intelligence in Robotics and Automation, Jacksonville, FI, USA, 20–23 June 2007; pp. 101–106.
[30]
Li, W.; Li, Y.Y.; Zhang, J.W. Fuzzy Color Extractor based Algorithm for Segmenting an Odor Source in Near Shore Ocean Conditions. Proceedings of IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), Hong Kong, China, 1–6 June 2008; pp. 2256–2261.
[31]
Li, W.; Lu, G.T.; Wang, Y.Q. Recognizing white line markings for vision-guided vehicle navigation by fuzzy reasoning. Patt. Recogn. Lett. 1997, 18, 771–780.
[32]
Li, W.; Jiang, X.J. Road recognition for navigation of an autonomous vehicle by fuzzy reasoning. Fuzzy Sets Syst. 1998, 93, 275–280.
