It seems the future has finally come. So, a team from the University of Bristol has created a new algorithm that will make robots much more “humane” than they are now. A new achievement of scientists, published in the journal Science Robotics, proves that in the near future robots will learn how to help a person, becoming practically indistinguishable from him.
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Inspired by an example from biology, researchers from the University of Bristol came up with the concept of a computer with a special soft substance that will mimic the work of the cardiovascular system.
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Guided by knowledge of its structure, researchersled by robotics professor Jonathan Rossiter, they successfully demonstrated a new mechanism that allowed them to integrate a new motion algorithm into three soft robots at once. In their article, the research team describes the functions of a conductive liquid receptor, which is an almost complete analogue of human blood and a new fundamental building block for a number of new generation robots.
According to Professor Rossiter’s report, already inin the near future, computers with soft matter could, if necessary, start all the most important processes that will occur in the "body" of the robot. In order for everything to work out, and the robot could make its first “meaningful” movements, soft matter will have to translate all the information received into the structure of the fluid tape, which would simulate the processes occurring in human blood. So, the action of a fluid tape will have to spread through the entire body of the robot so that the necessary signal can be detected by the corresponding receptor and can be transmitted to one or another artificial “nerve ending”.
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In order to explain the complex in simple terms,Professor Rossiter demonstrated to the public the robotic worm he created, which was programmed by an internal computer with soft matter.
A video of a soft robot worm was provided by techxplore.com
According to the professor, soft robots withtime can become even more alive: they will be able to independently adapt to the environment and demonstrate the diversity of behavior observed in the natural world.