Bug’s Life: So They Put A Tiny Camera On A Beetle And Captured This Footage [Video]

They have developed a tiny wireless steerable camera that can be fitted to an insect – in this case, a beetle – which then streams video to a smartphone.

Dubbed the ‘GoPro for Beetles’ by some, the camera can pivot 60 degrees thanks to a mechanical arm, and weighs around 250 milligrams.

That’s about a tenth of the weight of a single playing card, in case you needed a comparison.

To mimic an animal’s vision, the researchers used a tiny, ultra-low-power black-and-white camera that can sweep across a field of view with the help of a mechanical arm. The arm moves when the team applies a high voltage, which makes the material bend and move the camera to the desired position. Unless the team applies more power, the arm stays at that angle for about a minute before relaxing back to its original position. This is similar to how people can keep their head turned in one direction for only a short period of time before returning to a more neutral position…

The camera and arm are controlled via Bluetooth from a smartphone from a distance up to 120 meters away, just a little longer than a football field.

The cameras were fitted to the back of two beetle species – a death-feigning beetle and a Pinacate beetle – that are known to carry loads far heavier than the camera itself.

Here’s a summary of how it all works:

If you’re worried about the beetles’ wellbeing, you might be pleased to know that they lived for at least a year after the experiment ended.

More from the research team:

“This is the first time that we’ve had a first-person view from the back of a beetle while it’s walking around. There are so many questions you could explore, such as how does the beetle respond to different stimuli that it sees in the environment?” [co-lead author Vikram] Iyer said.

“But also, insects can traverse rocky environments, which is really challenging for robots to do at this scale. So this system can also help us out by letting us see or collect samples from hard-to-navigate spaces.”

I possess neither the skills, not the patience, to attempt anything even remotely close to this.

Respect to the researchers.

More on their findings here.

[source: washingtonuni]

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