page_title: Robot fish
section_title: Control
hierarchical_section_title: Robot fish / Design / Control
caption_attribution_description: Robot Fish
context_page_description: A robot fish is a type of bionic robot, which has the shape and locomotion of a living fish. 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. Most robot fish are designed to emulate living fish which use Body-caudal fin propulsion. BCF robot fish can be divided into three categories: Single Joint, Multi-Joint, and smart material-based design. The most important parts of researching and developing robot fish are advancing their control and navigation, enabling them to '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.
context_section_description: 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.
  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.
  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.
  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.
caption: Multi-joint robotic fish
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