Scientists Develop Machine Octopus Eel Utilizing Two Neural Systems to Achieve Stronger Performance

2024-01-24

According to foreign media reports, although researchers have previously developed swimming robots similar to eels, they often simply replicate the actions of their biological counterparts. The AgnathaX machine is different in that it utilizes a simulated central and peripheral nervous system to achieve more powerful performance.

Inspired by the octopus eel, the AgnathaX was developed in collaboration with scientists from the Federal Institute of Technology in Lausanne, Switzerland (EPFL), Northeastern University of Japan, Mines-T é l é com Atlantique Institute in France, and the University of Shebk in Canada. Its design is to explore the ways in which the central and peripheral nervous systems of animals contribute to movement.

In the past, some scientists speculated that the central nervous system (brain and spinal cord) should be primarily responsible because the signals it generates can rhythmically move an animal's legs, fins, or wings. However, others believe that the peripheral nervous system (the nerves connecting the limbs of the body and the brain) plays a greater role, as the nerves in the moving limbs generate feedback signals that keep the rhythm going.

In fact, both nervous systems are important for movement, and AgnathaX has helped prove this. This articulated robot consists of 10 connected parts, each containing a motor, playing the role of a true octopus eel muscle. A onboard microprocessor serves as the central nervous system, sequentially activating motors to generate undulating swimming movements. The force sensors located on both sides of each segment simulate the peripheral nervous system by sensing the pressure of water as it moves along the segment. In true octopus eels, pressure sensitive cells in the skin also play a similar role.

When using motion tracking systems to analyze the movements of robots swimming in a pool, researchers found that when two neural systems work together, the robot performs better. That is to say, when scientists cut off communication between certain segments (simulating spinal cord disease), the feedback provided by the force sensor is still sufficient to maintain the overall swimming mode. When these sensors are disabled, the robot can also maintain swimming, relying entirely on the rhythm generated by its brain.

The co authors of this research paper Dr. Camillo Mello from EPFL said, "By utilizing a combination of central and peripheral components, robots can resist more neural interference and maintain high-speed swimming, rather than robots with only one component. We also found that force sensors in the robot skin, as well as physical interactions between the robot body and water, provide useful signals for generating and synchronizing rhythmic muscle activity required for movement."

Now, people hope that the team's findings can lead to more powerful robots - for applications such as search and rescue or environmental monitoring - and even improve the treatment of human spinal cord injuries.

This paper was recently published in the journal Scientific Robotics.

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