The special drone model can bend itself when a collision occurs

This drone model is quite special because thanks to the timely flexibility of the collision with the surface when flying, damage and drone damage will no longer be a problem.

Today's drone models have a rather large design, especially cargo drone models, which are even more noticeable. Although the manufacturers already have multiple drone protection mechanisms when a collision like a wing guard occurs, the actual drone will still easily fail when it collides with hard surfaces.

A drone with flexible flexing capability will help reduce the impact of the collision.

To find a solution to this problem, a team of researchers from the Federal Institute of Technology in Lausanne, Switzerland, came up with an interesting solution, making drones more flexible and flexible. . More notably, the inspiration for this solution comes from the mother nature itself.

According to Slashgear, a drone with flexible flexing capability will help reduce the impact of the collision. However, this is really not good when the drone moves. Two contradictory issues forced researchers to find a complete solution. And the wasp has become an effective answer to this problem.

The wasps' wings have a certain hardness, ensuring easy movement of bees. However, when bees or their wings collide with any solid object, their wings will become more flexible and flexible to distribute the impact force, minimizing the risk of tearing the wings. Scientists call this "dual rigidity" and the key to the problem.

The drone model was tested by scientists including a flexible frame, flexible and hard core.

The drone model was tested by scientists including a flexible frame, flexible and hard core. The rigid frame is connected together around the magnet hard core. When there is a collision, the frame will be separated from the magnet, and thanks to its flexible bending ability, it absorbs all the impact force. After being separated, the frame returns to its original position thanks to the magnet's attraction.

Currently this is just an initial test and it is unclear whether the researchers commercialized this research. However, the research is very promising if applied to robots or other devices.