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Scientists Discover Way to Send Information into Black Holes Without Using Energy

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A Robotic Fish Revealed a Secret Why Real Fish Swim in Short Bursts

Many aquatic animals do not swim in a smooth, continuous way. Instead, they move in short bursts, pause briefly, and then swim again. This pattern is called intermittent locomotion or bout-and-glide swimming. You can clearly see this behavior in small fish like larval zebrafish, tadpoles, and even some adult fish.

For a long time, scientists have wondered:
Why do fish swim this way?
Is it just a habit, or does it save energy?
And what is happening inside the nervous system that controls this movement?

Answering these questions using live animals is extremely difficult. Fish are small, fast, and delicate. Measuring their internal muscle activity, neural signals, and energy use while they swim freely is a major technical challenge. To overcome this problem, researchers turned to an innovative solution: a robotic fish.

A research team from EPFL (École Polytechnique Fédérale de Lausanne), led by Xiangxiao Liu, developed a bio-inspired robot called ZBot. This robot mimics the body shape, movement patterns, and neural control logic of larval zebrafish. Using ZBot, scientists were able to study intermittent swimming in a controlled and repeatable way—and the results were surprising.

What Is Intermittent Swimming?

Intermittent swimming means moving in distinct swimming bouts followed by passive gliding. During a bout, the fish beats its tail rapidly to gain speed. During the glide, it stops moving its tail and simply coasts forward.

This is very different from continuous swimming, where the tail keeps moving all the time.

In nature, intermittent swimming is common in:

  • Larval and juvenile fish

  • Tadpoles

  • Some adult fish during cruising

  • Aquatic insects and larvae

But until now, scientists were not sure whether this style truly saves energy or how it is controlled by the nervous system.

Why Studying Real Fish Is So Hard

Live-animal experiments come with many challenges:

  • You cannot easily measure muscle efficiency inside a freely swimming fish

  • Neural signals are tiny and hard to record

  • Water flow conditions change constantly

  • Repeating the same exact movement is nearly impossible

Because of these limits, researchers often rely on computer simulations or simplified models. However, simulations cannot fully capture real-world water dynamics and mechanical losses.

This is where ZBot comes in.

Meet ZBot: A Robotic Zebrafish

ZBot is a bioinspired robotic fish designed to closely resemble larval zebrafish in both shape and movement. It includes:

  • A flexible body and tail similar to a real larva

  • Actuators that move like fish muscles

  • A neural network model inspired by zebrafish spinal circuits

  • Control parameters based on real kinematic recordings

ZBot does not just swim—it swims like a zebrafish. It can perform:

  • Short swimming bursts

  • Passive gliding phases

  • Turns and speed changes

  • Different tail-beating frequencies and amplitudes

This makes it an ideal tool for testing how swimming patterns affect speed, energy use, and efficiency.

Testing ZBot in Different Water Conditions

The researchers tested ZBot in two main flow regimes:

1. Viscous Flow

This condition is common for very small animals. Water feels “thicker,” and resistance is high.

2. Turbulent Flow

This is more typical for larger animals or faster swimming, where swirling currents dominate.

By testing both conditions, the team could see whether intermittent swimming works only in special cases or across a wide range of environments.

Key Findings: How Water Affects Movement

The experiments revealed some important patterns:

  • Viscous flow greatly reduced how far ZBot traveled

  • Turning angles were barely affected by water type

  • Tail-beating frequency and amplitude strongly influenced speed

  • Power consumption increased sharply during continuous swimming

These results helped separate the effects of water resistance from the effects of motor and actuator performance.

The Big Discovery: Intermittent Swimming Saves Energy

The most important result was clear and consistent:

Intermittent swimming lowers the energetic cost of transport across most achievable speeds.

In simple terms, ZBot used less energy per distance traveled when it swam in bursts with glides, compared to swimming continuously—both in viscous and turbulent water.

This confirmed that intermittent swimming is not just a behavioral habit. It is an energy-saving strategy.

A New Mechanism: Actuator Efficiency

Earlier studies suggested that intermittent swimming saves energy mainly because:

  • Gliding reduces drag

  • Passive motion costs no muscle power

While this is true, the ZBot experiments revealed something new and very important.

Better Use of Actuators

The robot’s motors (which act like fish muscles) are more efficient at certain operating points. During intermittent swimming:

  • Motors work at higher efficiency during short bursts

  • They avoid inefficient low-power continuous operation

  • Heat and electrical losses are reduced

In other words, intermittent locomotion shifts the actuators into a more efficient performance range.

This means the energy savings are not only about water physics—but also about how muscles or motors work internally.

Why This Matters for Biology

These findings help answer long-standing biological questions:

  • Why do larval fish naturally swim in bouts?

  • How does the nervous system optimize energy use?

  • Why is this behavior so common across species?

The results suggest that evolution may have favored intermittent swimming because it:

  • Reduces total energy cost

  • Matches muscle efficiency curves

  • Works well across different water conditions

This gives us a deeper understanding of how neural control, muscle mechanics, and fluid dynamics work together in living animals.

Implications Beyond Biology

The impact of this research goes far beyond fish.

For Robotics

  • Design of more energy-efficient underwater robots

  • Longer mission times with limited battery power

  • Smarter control strategies inspired by biology

For Engineering

  • Better actuator scheduling

  • Improved efficiency in cyclic machines

  • Insights into intermittent operation in motors and pumps

For Science

  • A new experimental platform to test locomotion theories

  • A bridge between neuroscience, biomechanics, and robotics

Conclusion: Small Bursts, Big Insights

By building and testing a fish-like robot, researchers uncovered a powerful principle of movement. Intermittent swimming is not only natural—it is smart.

The study shows that:

  • Bout-and-glide swimming is energetically efficient

  • The benefit holds across different flow regimes

  • Actuator efficiency plays a key role

  • Robotic models can reveal hidden biological mechanisms

ZBot proves that sometimes, to understand life, we need to build machines that move just like it. And in doing so, we learn not only how animals swim—but how efficiency itself is shaped by nature.

Reference: 

  • Xiangxiao Liu et al.
    •  
,
Energy efficiency and neural control of continuous versus intermittent swimming in a fishlike robot.Sci. Robot.11,eadw7868(2026).DOI:10.1126/scirobotics.adw7868

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