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article imageLooking to the insect world to design a new generation of robots

By Tim Sandle     Nov 6, 2020 in Science
A new high-speed amphibious robot has been developed. The inspiration for the design comes from the movements of cockroaches and lizards. As a result, the robot swims and runs on top of water and it can crawl across difficult terrain.
The new robot design comes from Ben-Gurion University of the Negev researchers and the mechanics of the robot are based on observations taken from the natural world. The resultant machine is called the AmphiSTAR robot.
The robot is a wheeled device that is also equipped with four propellers, positioned underneath. The axes are tilted using the sprawl mechanism. The function of the propellers is to serve as wheels over ground and also as fins, when the robot is required to move across water.
When swimming, the robot can achieve speeds of 1.5 meters per second. This is made possible through the use of air tanks, that enable the robot to float and transition smoothly. On rough terrain, the prototype machine has been tested across gravel, grass and concrete, reaching speeds of 3.6 meters per second (equivalent to 3.3 miles per hour).
The robot can be seen in the following video:
As a further example of this type of insect-inspired functionality, Purdue University researchers have develop a rectangular robot which is only as tiny as a few human hairs. The robot can travel throughout a colon by undertaking back flips. So far the technologists have demonstrated the capabilities of the robot in live animal models. It is hoped that the device will be suitable for human trials in the near future.
The main application of the robot will be to transport drugs to key locations within the colon. The concept study has bene published in a science publication called Micromachines: "A Tumbling Magnetic Microrobot System for Biomedical Applications".
Taking a different tract, zoologists from the University of Cologne have studied the nervous systems of insects. This inquiry was undertaken to assess the principles of biological brain computation. It is hoped the research will have important implications for machine learning and artificial intelligence.
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