Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-14T15:15:04.202Z Has data issue: false hasContentIssue false
  • English
  • Français

Development and target following of vision-based autonomous robotic fish

Published online by Cambridge University Press:  10 March 2009

Yonghui Hu ,
Wei Zhao ,
Guangming Xie  and
Long Wang
Yonghui Hu*
Affiliation:
Intelligent Control Laboratory, Department of Mechanics and Space Technologies, College of Engineering, Peking University, Beijing 100871, P. R. China
Wei Zhao
Affiliation:
Intelligent Control Laboratory, Department of Mechanics and Space Technologies, College of Engineering, Peking University, Beijing 100871, P. R. China
Guangming Xie
Affiliation:
Intelligent Control Laboratory, Department of Mechanics and Space Technologies, College of Engineering, Peking University, Beijing 100871, P. R. China
Long Wang
Affiliation:
Intelligent Control Laboratory, Department of Mechanics and Space Technologies, College of Engineering, Peking University, Beijing 100871, P. R. China
*
*Corresponding author. E-mail: huyhui@gmail.com
Get access Rights & Permissions [Opens in a new window]

Summary

A novel ostraciiform swimming, vision-based autonomous robotic fish is developed in this paper. Its feasibility and capability are shown by implementing a dynamic target following task in a swimming pool. Inspired by boxfish that is highly stable and fairly maneuverable, the robotic fish is designed and constructed by locating multiple propulsors peripherally around a rigid body. Swimming locomotion of the robotic fish is achieved through harmonic oscillations of the tail and pectoral fins. The forces and moments acting on the fins and body are analyzed and the governing motion equations are derived. Through coordinating the movements of the propulsors, several typical swimming patters are empirical designed and realized. A digital camera is integrated in the robotic fish, and the visual information is processed with the embedded microcontroller. To treat the degradation of underwater image, a continuously adaptive mean shift (Camshift) algorithm is modified to keep visual lock on the moving target. A fuzzy logic controller is designed for motion regulation of a hybrid swimming pattern, which employs synchronized pectoral fins for thrust generation and tail fin for steering. A simple target following task is designed via an autonomous robotic fish swimming after a manually controlled robotic fish with fixed distance. The swimming performance of the robotic fish is tested and the effectiveness of the proposed target following method is verified experimentally.

Keywords

Autonomous underwater vehiclesBiomimetic robotic fishSwimming patternVisual trackingTarget following
Type
Article
Information
Robotica , Volume 27 , Issue 7 , December 2009 , pp. 1075 - 1089
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Bandyopadhyay, P. R., “Trends in biorobotic autonomous undersea vehicles,” IEEE J. Oceanic Eng. 30 (1), 109–139 (2005).Google Scholar
2.Fish, F. E. and Lauder, G. V., “Passive and active flow control by swimming fishes and mammals,” Annu. Rev. Fluid Mech. 38, 193–224 (2006).CrossRefGoogle Scholar
3.Sfakiotakis, M., Lane, D. M. and Bruce, J.Davies, C., “Review of fish swimming modes for aquatic locomotion,” IEEE J. Oceanic Eng. 24 (2), 237–252 (1999).CrossRefGoogle Scholar
4.Lauder, G. V. and Drucker, E. G., “Morphology and experimental hydrodynamics of fish fin control surfaces,” IEEE J. Oceanic Eng. 29 (3), 556–571 (2004).CrossRefGoogle Scholar
5.Lauder, G. V. and Tytell, E. D., “Hydrodynamics of undulatory propulsion,” Fish Biomech. 23, 425–468 (2006).Google Scholar
6.Westneat, M. W., Thorsen, D. H., Walker, J. A. and Hale, M. E., “Structure, function and neural control of pectoral fins in fishes,” IEEE J. Oceanic Eng. 29 (3), 674–683 (2004).CrossRefGoogle Scholar
7.Triantafyllou, M. S. and Triantafyllou, G. S., “An efficient swimming machine,” Sci. Am. 272 (3), 64–70 (1995).Google Scholar
8.Barrett, D., Grosenbaugh, M. and Triantafyllou, M., “The Optimal Control of a Flexible Hull Robotic Undersea Vehicle Propelled by an Oscillating Foil,” Proceedings of 1996 IEEE AUV Symposium (Monterey, CA, 1996) pp. 1–9.Google Scholar
9.Anderson, J. M. and Kerrebrock, P. A., “The Vorticity Control Unmanned Undersea Vehicle (VCUUV)–-An Autonomous Vehicle Employing Fish Swimming Propulsion and Maneuvering,” Proceedings of 10th International Symposium on Unmanned Untethered Submersible Technology (Durham, New Hampshire, 1997) pp. 189–195.Google Scholar
10.Mason, R. and Burdick, J., “Experiments in Carangiform Robotic Fish Locomotion,” Proceedings of International Conference on Robotics and Automation (San Francisco, CA, 2000) pp. 428–435.Google Scholar
11.Hirata, T., Welcome to fish robot home page (2000). Available at: http://www.nmri.go.jp/eng/khirata/fish/.Google Scholar
12.Liu, J., Hu, H. and Gu, D., “A Hybrid Control Architecture for Autonomous Robotic Fish,” Proceedings of International Conference on Intelligent Robots and Systems (Beijing, 2006) pp. 312–317.Google Scholar
13.Kato, N., “Control performance in the horizontal plane of a fish robot with mechanical fins,” IEEE J. Oceanic Eng. 25 (1), 121–129 (2000).CrossRefGoogle Scholar
14.Low, K. H., “Locomotion Consideration and Implementation of Robotic Fish with Modular Undulating Fins: Analysis and Experimental Study,” Proceedings of International Conference on Intelligent Robots and Systems (Beijing, 2006) pp. 2424–2429.Google Scholar
15.Hu, Y., Wang, L., Zhao, W., Wang, Q. and Zhang, L., “Modular Design and Motion Control of Reconfigurable Robotic Fish,” Proceedings of International Conference on Decision and Control (New Orleans, LA, 2007) pp. 5156–5161.Google Scholar
16.Fish, F. E., Lauder, G. V., Mittal, R., Techet, A. H., Triantafyllou, M. S., Walker, J. A. and Webb, P. W., “Conceptual Design for the Construction of a Biorobotic AUV Based on Biological Hydrodynamics,” Proceedings of 13th International Symposium on Unmanned Untethered Submersible Technology, New Hampshire (Durham, New Hampshire, 2003).Google Scholar
17.Colgate, J. E. and Lynch, K. M., “Mechanics and control of swimming: A review,” IEEE J. Oceanic Eng. 29 (3), 660–673 (2004).Google Scholar
18.Kelly, S. D., Mason, R. J., Anhalt, C. T., Murray, R. M. and Burdick, J.W., “Modeling and Experimental Investigation of Carangiform Locomotion for Control,” Proceedings of American Control Conference (Philadelphia, PA, 1998) pp. 1271–1276.Google Scholar
19.McIsaac, K. A. and Ostrowski, J. P., “Experiments in Closed-Loop Control for an Underwater Eel-Like Robot,” Proceedings of IEEE International Conference on Robotics Automation (Washington, DC, 2002) pp. 750–755.Google Scholar
20.Morgansen, K. A., La Fond, T. M. and Zhang, J. X., “Agile Maneuvering for Fin-Actuated Underwater Vehicles,” Proceedings of International Symposium on Communications, Control and Signal Processing (Marrakech, Morocco, 2006).Google Scholar
21.Yu, J., Wang, L. and Tan, M., “Geometric optimization of relative link lengths for biomimetic robotic fish,” IEEE Trans. Robot. 23 (2), 382–386 (2007).Google Scholar
22.Zhang, D., Wang, L., Yu, J. and Tan, M., “Coordinated transport by multiple biomimetic robotic fish in underwater environment,” IEEE Trans. Control Syst. Technol. 15 (4), 658–671 (2007).Google Scholar
23.Gordon, M., Hove, J., Webb, P. and Weihs, D., “Boxfishes as unusually well-controlled autonomous underwater vehicles,” Physiol. Biochem. Zool. 74 (6), 663–671 (2000).Google Scholar
24.Hove, J. R., OBryan, L. M., Gordon, M. S., Webb, P. W. and Weihs, D., “Boxfishes (teleostei: Ostraciidae) as a model system for fishes swimming with many fins: Kinematics,” J. Exp. Biol. 204 (8), 1459–1471 (2001).CrossRefGoogle Scholar
25.Kodati, P. and Deng, X., “Experimental Studies on the Hydrodynamics of a Robotic Ostraciiform Tail Fin,” Proceedings of International Conference on Intelligent Robots and Systems (Beijing, 2006) pp. 5418–5423.Google Scholar
26.Lachat, D., Crespi, A. and Ijspeert, A. J., “Boxybot: A Swimming and Crawling Fish Robot Controlled by a Central Pattern Generator,” Proceedings of IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (Pisa, Tuscany, 2006) pp. 643–648.Google Scholar
27.Lauder, G. V. and Madden, P. G. A., “Learning from fish: Kinematics and experimental hydrodynamics for roboticists,” Int. J. Automat. Comput. 3 (4), 325–335 (2006).Google Scholar
28.Fossen, T., Guidance and Control of Ocean Vehicles (John Wiley & Sons Ltd., Chichester, UK 1994).Google Scholar
29.Healey, A. J., Rock, S. M., Cody, S., Miles, D. and Brown, J. P., “Toward an improved understanding of thruster dynamics for underwater vehicles,” IEEE J. Oceanic Eng. 20 (4), 354–361 (1995).CrossRefGoogle Scholar
30.Kocak, D. M. and Caimi, F. M., “The current art of underwater imaging–-with a glimpse of the past and vision of the future,” Marine Technol. Soc J. 39 (3), 5–26 (2005).CrossRefGoogle Scholar
31.Comaniciu, D., Ramesh, V. and Meer, P., “Kernel-based object tracking,” IEEE Trans. Pattern Anal. Mach. Intell. 25 (5), 564–575 (2003).CrossRefGoogle Scholar
32.Bradski, G. R., “Computer video face tracking for use in a perceptual user interface,” Intel Technol. J. (1998) (2nd Quarter).Google Scholar