While humans may struggle to navigate a murky, turbid underwater environment, weakly electric fish can do so with ease. These aquatic animals are specially adapted to traverse obscured waters without relying on vision; instead, they sense their environment via electric fields. Now, researchers are attempting to adapt these electrosensing techniques to improve underwater robotics.

Scientists have spent years studying how weakly electric fish—including the knife fish and elephant nose fish—utilize electricity for navigation. These fish have specialized electric organs that discharge small voltages into the surrounding water, creating their own personal electric fields. Nearby objects cause slight disruptions to these fields, which the fish detect with sensitive organs on their skin called electroreceptors. As a fish swims around, it can sense an object from multiple viewpoints to learn more about its features — all without gaining any visual perspective. Fully understanding the mechanisms of this unique adaptation that allows fish to orient themselves and navigate in complete darkness could help underwater robots do the same. 

Lorenzo Baldassari and Andrea Scapin of the Swiss Federal Institute of Technology in Zürich were intrigued by the possibility of modeling the way in which weakly electric fish perceive their environments through electricity. In a paper publishing on Thursday in the SIAM Journal on Imaging Sciences, Baldassari and Scapin introduce an innovative algorithm for observing objects via electrosensing that is based on the real behavior of weakly electric fish. “These animals are an ideal subject for developing new bio-inspired imaging techniques,” Baldassari said.  {module INSIDE STORY}

Weakly electric fish’s impressive sensing capabilities inspired the duo to develop an algorithm that could emulate how the fish detect and locate a target based on the distribution of electrical current over their skin. They sought to create a mathematical simulation of a fish that would swim in circular paths around a target object and incorporate a recognition algorithm that could synthesize the electrosensed information to determine what object the fish was near. 

The algorithm needed to know the possible shapes of this object, so Baldassari and Scapin established a dictionary of seven standard shapes: a circle, ellipse, triangle, bent ellipse, curved triangle, gingerbread man, and drop. In their simulation, a fish swam around a randomly-selected object from the dictionary — this theoretical fish did not know beforehand what kind of object it would encounter, just like a real fish does not know about its environment before electrosensing it. The algorithm’s goal was then to use the data collected by the simulated fish to determine which dictionary element matched the target object. 

The most important mathematical quantity in this simulation was the length-scale, or the ratio between the target’s size and the distance between the fish and the target. As the length-scale increases—i.e., the fish moves closer to the target—the size of the electrical disturbance from the target also increases, providing a higher-resolution view of the object. Previous studies involving electrosensing algorithms only utilized measurements taken at one length-scale. To improve upon this technique, Baldassari and Scapin had their modeled fish take multiple circular orbits at different distances from the target, thereby obtaining measurements at several different length-scales. This multi-scale approach combines information that the theoretical fish gathers at different distances from the object to gain a more accurate understanding of its features. But the advantages of multi-scale did not come easily. “The most difficult aspect of this work was choosing a proper way for combining the information at multiple length-scales,” Scapin said. The authors attempted multiple methods before finally landing on a strategy for combining the information that did not have any major drawbacks.  

For the recognition algorithm that worked best, the first step was to measure and record the electric perturbation from the target that the fish detected upon each orbit. A matching procedure then compared this data to the dictionary of possible shapes, giving a numerical score to indicate the degree of similarity between the unknown target and the dictionary item that it most resembled. This score was saved for later combination. “The strong point of our recognition algorithm is that when performing the classifications orbit-by-orbit, previous comparisons are incorporated in the selection of the best matching shape,” Scapin said. “This leads to an enhancement in the recognition.” The team combined the numerical scores from different orbits to create a belief assignment that denoted which dictionary shape the algorithm determined was the best match for the target, and how confident it was in that determination.

To test their recognition algorithm, the authors simulated a fish with 1,024 electroreceptors evenly distributed on its body that made three circular orbits around an object, then recorded how often it was able to correctly identify the target. This new multi-scale approach had a higher rate of correct recognition than previous single-scale approaches; although fusing the results from different length-scales did not produce the best outcome every single time, it was the most effective approach overall. According to these results, future advancements in electrosensing algorithms will be most successful if they continue to incorporate multi-scale measurements.

Baldassari and Scapin’s new electrosensing algorithm has the potential to advance navigation in underwater robotics, though applying their procedure to real devices would require extending the algorithm to handle three dimensions. However, the potential rewards for such an effort are tantalizing. “Building autonomous robots with electrosensing technology may supply unexplored navigation, imaging, and classification capabilities, especially when sight is unreliable due to the turbidity of the surrounding waters or poor lighting conditions,” Baldassari said. Electrosensing robots could enable a deeper study of areas of the ocean that are inaccessible to human divers, advancing undersea exploration further than ever before.

Data from Arecibo Observatory in Puerto Rico has been used to help detect the first possible hints of low-frequency disturbances in the curvature of space-time.

The results were presented yesterday at the 237th meeting of the American Astronomical Society, which was held virtually, and are published in The Astrophysical Journal Letters. Arecibo Observatory is managed by the University of Central Florida for the National Science Foundation under a cooperative agreement.

The disturbances are known as gravitational waves, which ripple through space as a result of the movement of incredibly massive objects, such as black holes orbiting one another or the collision of neutron stars.

It's important to understand these waves as they provide insight into the history of the cosmos and expand researchers' knowledge of gravity past current limits of understanding.

Although the gravitational waves are stretching and squeezing the fabric of space-time, they don't impact humans and any changes in the relative distances between objects would change the height of a person by less than one one-hundredth the width of a human hair, says Joseph Simon, a postdoctoral associate in the Center for Astrophysics and Space Astronomy at the University of Colorado Boulder. {module INSIDE STORY}

Simon presented the findings to the society today, is the lead researcher of the paper, and is a member of the North American Nanohertz Observatory for Gravitational Waves, or NANOGrav, the team that performed the research.

NANOGrav is a group of more than 100 astronomers from across the U.S. and Canada whose common goal is to study the universe using low-frequency gravitational waves.

In 2015, NSF's Laser Interferometer Gravitational-Wave Observatory (LIGO) made the first direct observation of high-frequency gravitational waves using interferometry, a measurement method that uses the interference of electromagnetic waves.

The new findings made by NANOGrav researchers are unique because the astronomers found possible hints of low-frequency gravitational waves by using radio telescopes since they cannot be detected by LIGO. Both frequencies are important for understanding the universe.

Key to the research were two NSF-funded instruments - Green Bank Telescope in West Virginia and Arecibo Observatory in Puerto Rico.

Arecibo Observatory, with its 1,000-foot diameter dish, provided very precise data, while the Green Bank Telescope, which has much larger sky coverage, sampled a wider range of information needed to discriminate gravitational wave perturbations from other effects, Simon says.

"We time roughly half the pulsars with each telescope," he says. "Each telescope provides about half of our total sensitivity in a complementary way."

Although the researchers used Arecibo data for the study, they are no longer able to make observations with it since the observatory collapsed in December following broken cables in August and November.

"It was a truly horrible day when the telescope collapsed," Simon says. "It feels like the loss of a good friend, and we are so saddened for our friends and colleagues in Puerto Rico. Going forward, we hope to increase the amount of time we use on the Green Bank Telescope to at least partially compensate for Arecibo's loss. Another large collecting area radio telescope must be built in the U.S. soon if we want this research area to flourish."

The researchers were able to detect possible hints of low-frequency gravitational waves by using the telescopes to study signals from pulsars, which are small, dense, rotating stars that send out pulses of radio waves at precise intervals toward Earth.

This regularity makes them useful in astronomical study, and they are often referred to as the universe's timekeepers.

Gravitational waves can interrupt their regularity, causing deviations in pulsar signals arriving on Earth, thus indicating the position of the Earth has shifted slightly.

By studying the timing of the regular signals from many pulsars scattered over the sky at the same time, known as a "pulsar timing array," NANOGrav was able to detect minute changes in the Earth's position possibly due to gravitational waves stretching and shrinking space-time.

NANOGrav was able to rule out some effects other than gravitational waves, such as interference from the matter in the solar system or certain errors in the data collection.

To confirm direct detection of a signature from low-frequency gravitational waves, NANOGrav researchers will have to find a distinctive pattern in the signals between individual pulsars. At this point, the signal is too weak for such a pattern to be distinguishable, according to the researchers.

Boosting the signal requires NANOGrav to expand its dataset to include more pulsars studied for even longer lengths of time, which will increase the array's sensitivity. In addition, pooling NANOGrav's data together with those from other pulsar timing array experiments, a joint effort by the International Pulsar Timing Array, may reveal such a pattern. The International Pulsar Timing Array is a collaboration of researchers using the world's largest radio telescopes.

At the same time, NANOGrav is developing techniques to ensure the detected signal could not be from another source. They are producing supercomputer simulations that help test whether the detected noise could be caused by effects other than gravitational waves, in order to avoid false detection.

"It is incredibly exciting to see such a strong signal emerge from the data," Simon says. "However, because the gravitational-wave signal we are searching for spans the entire duration of our observations, we need to carefully understand our noise. This leaves us in a very interesting place, where we can strongly rule out some known noise sources, but we cannot yet say whether the signal is indeed from gravitational waves. For that, we will need more data."

Benetge Perera, a scientist at Arecibo Observatory who is a specialist in using observations of pulsars for the detection of gravitational waves, says the research aims to open a new window in the spectrum of gravitational wave frequencies.

"A low-frequency gravitational wave detection would enhance our understanding of supermassive black hole binaries, galaxy evolution, and the universe," says Perera, who is also a member of NANOGrav.

He says that despite the collapse of Arecibo Observatory, there are still many archived data to pore through to continue to learn about gravitational waves.

"Arecibo was very important as its timing data provided about 50 percent of NANOGrav's sensitivity to gravitational waves," he says. "I want to ensure that the sensitive data we collected before Arecibo's collapse has the highest possible scientific impact."