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Contents

   



(Top)
 


1 Design  



1.1  Design inspiration  





1.2  Control  







2 Uses  



2.1  Studying fish behavior  





2.2  Toys  





2.3  Application on AUV  





2.4  Education  







3 Examples  





4 References  














Robot fish






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From Wikipedia, the free encyclopedia
 

(Redirected from Robotic fish)

Jessiko robot fish on France Pavilion at Yeosu 2012 World Expo

Arobot fish is a type of bionic robot that has the shape and locomotion of a living fish. Most robot fish are designed to emulate living fish which use body-caudal fin (BCF) propulsion, and can be divided into three categories: single joint (SJ), multi-joint (MJ) and smart material-based "soft-body" design.

Since the Massachusetts Institute of Technology first published research on them in 1989, there have been more than 400 articles published about robot fish. According to these reports, approximately 40 different types of robot fish have been built, with 30 designs having only the capability to flip and drift in water. The most important parts of researching and developing robot fish are advancing their control and navigation, enabling them to interact and "communicate" with their environment, making it possible for them to travel along a particular path, and to respond to commands to make their "fins" flap.[1][2][3]

Design[edit]

The basic biomimetic robotic fish is made up of three parts: a streamlined head, a body, and a tail.

Design inspiration[edit]

Eel and fish locomotion

Engineers often focus on functional design. For example, designers attempt to create robots with flexible bodies (like real fish) that can exhibit undulatory motion. This kind of body enables the robot fish to swim similar to the way live fish swim, which can adapt and process a complicated environment. The first robot fish (MIT's RoboTuna) was designed to mimic the structure and dynamic properties of a Tuna. In an attempt to gain thrust and maneuvering forces, robot fish control systems are capable of controlling the body and caudal fin, giving them a wave-like motion.[5][6]

In order to control and analyze robotic fish movement, researchers study the shape, dynamic model and lateral movements of the robotic tail. One of the many tail shapes found on robot fish is lunate, or crescent shaped. Some studies show this kind of tail shape increases swimming speeds and creates a high-efficiency robot fish.

The posterior tail creates thrust force, making it one of the most important parts of the robot fish. Living fish have powerful muscles that can generate lateral movements for locomotion while the head remains in a relatively motionless state. Thus, researchers have focused on tail kinematics when developing robot fish motion.[7]

Slender-body theory is often used when studying robot fish locomotion. The mean rate of work of the lateral movements is equal to the sum of the mean rate of work available for producing the mean thrust and the rate of shedding of kinetic energy of lateral fluid motions. The mean thrust can be calculated entirely from the displacement and swimming speed at the trailing edge of the caudal fin.[8] This simple formula is used when calculating the locomotion of both robot and living fish.

Realistic Propulsion Systems can help improve autonomous maneuvering and exhibit a higher level of locomotion performance. A diverse option of fins can be used in the creation of robot fish to achieve this goal. By including pectoral fins, robot fish can perform force vectoring and perform complex swimming behaviors instead of forward swimming only.[9]

Control[edit]

Multi-joint robotic fish

The shapes and sizes of fins vary drastically in living fish, but they all help to accomplish a high level of propulsion through the water. In order for robot fish to achieve the same type of rapid and maneuverable propulsion, robot fish need multiple control surfaces. The propulsive performance is related to the position, mobility, and hydrodynamic characteristics of the control surfaces.[10]

The key to controlling a multi-joint robotic fish is creating a simplified mechanism that is able to generate a reasonable amount of control. Designers should consider some important factors, including lateral body motions, kinematic data and anatomical data. When designers mimic a BCF-type robot fish, the link-based body wave of the robot fish must provide motions similar to that of a living fish. This kind of body wave-based swimming control should be discrete and parameterized for a specific swimming gait. Ensuring swimming stability gait can be difficult, and transitioning smoothly between two different gaits can be tricky in robot fish.[11]

A central neural system known as a "Central Pattern Generator" (CPGs) can govern multilink robotic fish locomotion. The CPG is located in every segment, and can connect and stimulate contracting or stretching muscles. The cerebrum, the most anterior part of the brain in vertebrates, can control signal inputs to startup, stop and turn. After the systems form a steady locomotion, the signal from the cerebrum stops and the CPGs can produce and modulate locomotion patterns.[citation needed]

Similar to their role in living fish, neural networks are used to control robot fish. There are several key points in the design of bionic neural networks. First, the bionic propeller adopts one servomotor to drive a joint while the fish has two group muscles in each joint. Designers can implement one CPG in each segment to control the corresponding joint. Second, a discrete computational model stimulates the continuous biological tissues. Finally, the connection lag time between neurons determines the intersegmental phase lag. The lag time function in the computational model is necessary.[12]

Uses[edit]

Studying fish behavior[edit]

Achieving a consistent response is a challenge in animal behavioral studies when live stimuli are used as independent variables. To overcome this challenge, robots can be used as consistent stimuli for testing hypotheses while avoiding large animal training and use. The controllable machines can be made to "look, sound, or even smell" like animals. We can obtain a better perception of animal behavior by turning to robot use in place of live animals because robots can produce a steady response in a set of repeatable actions. Moreover, with various field deployments and a greater degree of independence, robots hold the promise of assisting behavioral studies in the wild.[13][self-published source?]

Toys[edit]

A simple robot fish consisting of a flexible visco-elastic body

Toy robot fish are the most common robot toys on the market. they are most commonly used for entertainment, although some are used for research. The design of these toys are simple and inexpensive. They are usually divided into two categories: automatic cruise robot fish and controlled movement robot fish. The simplest ones consist of a soft body (MJ), motor (tail) and head (basic electric control element). They use a battery to provide energy for the motor to produce movement and use the remote control systems to achieve the power of steering. In contrast, the complexity of toys and robot fish, with the purpose of research, is almost the same. They are not only fully automated, but can simulate fish behavior. For example, if you put a foreign object in the water with the robot fish, it will produce a movement similar to that of a real fish. It will move away from the foreign object and the speed of swimming will increase. It exhibits a state of shock and confusion to the foreign object much like a real fish would. Robot fish record this type of behavior in advance.[14]

Application on AUV[edit]

Military defense and marine protection are of rising concern in the research field. As missions become more complicated, high-performance Autonomous underwater vehicle (AUVs) become necessary. AUVs require fast propulsion and multidirectional maneuverability. Robotic fish are more competent than current AUVs propelled by motion because the fish is a paradigm of bio-inspired AUV. Like living fish, robot fish can operate in complex environments. They can not only perform underwater exploration and discover new species, but they can also salvage and set up underwater facilities. When operating in dangerous environments, robot fish display a heightened performance when compared to other machines. For example, in the coral zone, soft robotic fish can better cope with the environment. Unlike existing AUVs which are non-flexible, robot fish can access narrow caves and tunnels.[15][16]

Education[edit]

Besides their vast potentials for research, robotic fish also show many opportunities to engage students and the general public. Bio-inspired robots are valuable and effective, and can attract students to various areas of science, technology, engineering and math. Robotic fish have been used as auxiliary educational tools all over the world. For example, thousands of youth were attracted to the carp-like robots during a recent exhibit at London Aquarium. Scientists and other researchers have presented various kinds of robotic fish at many outreach programs, including the first and second USA Science and Engineering Festivals, in 2010 and 2012, respectively. At these events, visitors were given the opportunity not only to see the robotic fish in action, but also interacted with the lab members to understand the technology and its applications.[17]

Examples[edit]

"Charlie", a robotic catfish built by the CIA
Robotic Fish: iSplash-II

References[edit]

  1. ^ Yu, Junzhi; Tan, Min (2015). "Design and Control of a Multi-joint Robotic Fish". In Du, Ruxu; Li, Zheng; Youcef-Toumi, Kamal; Valdivia y Alvarado, Pablo (eds.). Robot Fish: Bio-inspired Fishlike Underwater Robots. Springer Tracts in Mechanical Engineering. pp. 93–117. doi:10.1007/978-3-662-46870-8_4. ISBN 978-3-662-46869-2.
  • ^ Yu, Junzhi; Wang, Chen; Xie, Guangming (2016). "Coordination of Multiple Robotic Fish with Applications to Underwater Robot Competition". IEEE Transactions on Industrial Electronics. 63 (2): 1280–8. doi:10.1109/TIE.2015.2425359. S2CID 31599369.
  • ^ Nguyen, Phi Luan; Lee, Byung Ryong; Ahn, Kyoung Kwan (2016). "Thrust and Swimming Speed Analysis of Fish Robot with Non-uniform Flexible Tail". Journal of Bionic Engineering. 13: 73–83. doi:10.1016/S1672-6529(14)60161-X. S2CID 110144051.
  • ^ Zhang, Daibing; Hu, Dewen; Shen, Lincheng; Xie, Haibin (2008). "Design of an artificial bionic neural network to control fish-robot's locomotion". Neurocomputing. 71 (4–6): 648–54. doi:10.1016/j.neucom.2007.09.007.
  • ^ Wang, Tianmiao; Wen, Li; Liang, Jianhong; Wu, Guanhao (2010). "Fuzzy Vorticity Control of a Biomimetic Robotic Fish Using a Flapping Lunate Tail". Journal of Bionic Engineering. 7: 56–65. doi:10.1016/S1672-6529(09)60183-9. S2CID 135741678.
  • ^ Butail, Sachit; Polverino, Giovanni; Phamduy, Paul; Del Sette, Fausto; Porfiri, Maurizio (2014). "Influence of robotic shoal size, configuration, and activity on zebrafish behavior in a free-swimming environment". Behavioural Brain Research. 275: 269–80. doi:10.1016/j.bbr.2014.09.015. PMID 25239605. S2CID 20755024.
  • ^ Nguyen, Phi Luan; Do, Van Phu; Lee, Byung Ryong (2013). "Dynamic Modeling of a Non-Uniform Flexible Tail for a Robotic Fish". Journal of Bionic Engineering. 10 (2): 201–209. doi:10.1016/S1672-6529(13)60216-4. S2CID 137685845.
  • ^ Nguyen, Phi Luan; Lee, Byung Ryong; Ahn, Kyoung Kwan (2016). "Thrust and swimming speed analysis of fish robot with non-uniform flexible tail". Journal of Bionic Engineering. 1: 73–83. doi:10.1016/S1672-6529(14)60161-X. S2CID 110144051.
  • ^ Ravalli, Andrea; Rossi, Claudio; Marrazza, Giovanna (2017). "Bio-inspired fish robot based on chemical sensors". Sensors and Actuators B: Chemical. 239: 325–9. doi:10.1016/j.snb.2016.08.030.
  • ^ Siddall, R; Kovač, M (2014). "Launching the AquaMAV: Bioinspired design for aerial–aquatic robotic platforms". Bioinspiration & Biomimetics. 9 (3): 031001. Bibcode:2014BiBi....9c1001S. doi:10.1088/1748-3182/9/3/031001. hdl:10044/1/19963. PMID 24615533. S2CID 21175991.
  • ^ Nguyen, Phi Luan; Do, Van Phu; Lee, Byung Ryong (2013). "Dynamic Modeling and Experiment of a Fish Robot with a Flexible Tail Fin". Journal of Bionic Engineering. 10: 39–45. doi:10.1016/S1672-6529(13)60197-3. S2CID 109405322.
  • ^ Zhang, Daibing. "Design of an artificial bionic neural network to control fish-robot's locomotion". DocSlide.
  • ^ "RoboTuna". 11 September 2009.
  • ^ https://www.youtube.com/watch?v=31E8ywyUCrw[full citation needed]
  • ^ Liu, Jindong; Hu, Huosheng (2010). "Biological Inspiration: From Carangiform Fish to Multi-Joint Robotic Fish". Journal of Bionic Engineering. 7: 35–48. CiteSeerX 10.1.1.193.4282. doi:10.1016/S1672-6529(09)60184-0. S2CID 11802468.
  • ^ Wen, L; Wang, T M; Wu, G H; Liang, J H (2012). "Hydrodynamic investigation of a self-propelled robotic fish based on a force-feedback control method". Bioinspiration & Biomimetics. 7 (3): 036012. Bibcode:2012BiBi....7c6012W. doi:10.1088/1748-3182/7/3/036012. PMID 22556135. S2CID 6565585.
  • ^ Wang, Jianxun (2014). Robotic fish: development, modeling, and application to mobile sensing (PhD thesis). Michigan State University. OCLC 921153799.
  • ^ "Charlie: CIA's Robotic Fish — Central Intelligence Agency". www.cia.gov. Archived from the original on August 16, 2013. Retrieved 12 December 2016.
  • ^ "Archived copy". Archived from the original on 2016-11-29. Retrieved 2016-12-12.{{cite web}}: CS1 maint: archived copy as title (link)[full citation needed]
  • ^ http://www.robotic-fish.net/index.php?lang=en&id=robots#top[full citation needed]
  • ^ http://www.computerweekly.com/news/2240086124/University-of-Essex-robotic-fish-enter-IET-awards[full citation needed]
  • ^ http://www.robotswim.com/index.php?id=jessiko&id2=projet&lan=en[full citation needed]
  • ^ Chowdhury, Abhra Roy (2014). Modeling and Control of a Bioinspired Robotic Fish Underwater Vehicle Next Generation Underwater Robots (PhD Thesis).[permanent dead link]
  • ^ https://www.telegraph.co.uk/technology/3345303/Robot-koi-carp-designed-to-get-up-close-and-friendly-with-real-fish.html[full citation needed]
  • ^ "High-Speed Robotic Fish | iSplash". isplash-robot. Retrieved 2017-01-07.
  • ^ "iSplash-II: Realizing Fast Carangiform Swimming to Outperform a Real Fish" (PDF). Robotics Group at Essex University. Archived from the original (PDF) on 2015-09-30. Retrieved 2015-09-29.
  • ^ "iSplash-I: High Performance Swimming Motion of a Carangiform Robotic Fish with Full-Body Coordination" (PDF). Robotics Group at Essex University. Archived from the original (PDF) on 2015-09-30. Retrieved 2015-09-29.

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