Andres Arrieta, an assistant professor of mechanical engineering at Purdue University says drones and self-driving cars might actually detect and avoid objects better if they would process sensory information faster.
Drones can navigate in dangerous environments and for cars to prevent accidents caused by human error because they will have better sensing capabilities. The current state-of-the-art sensor technology of drones and self-driving cars does not process data fast enough.
Researchers would not have to create a radioactive spider to give autonomous machines a "Spiderman" type sensing ability, instead, the Purdue researchers have developed sensors that are inspired by bats, birds, spiders and other animals, whose actual senses are nerve endings linked to special neurons called mechanoreceptors.
The nerve endings, mechanosensors, can only detect and process information that is essential to an animal's survival. They come in the form of cilia, hair or feathers.
"There is already an explosion of data that intelligent systems can collect-and this rate is increasing faster than what conventional computing would be able to process," said Arrieta, whose lab applies principles of nature to the design of structures, ranging from robots to aircraft wings.
"Nature doesn't have to collect every piece of data; it filters out what it needs," he said.
Many biological mechanosensors filter data, according to a threshold, such as changes in temperature or pressure. It all depends on the information that they receive from an environment.
A spider's mechanosensors are located on its legs when a spider's web vibrates at a frequency linked with prey or a mate, the mechanosensors detect it and it generates a reflex in the spider that reacts very fast. The mechanosensors would not detect a lower frequency, because it is not important to their survival.
In real life, these forces would be linked with a certain object that an autonomous machine needs to avoid. But the sensors that the researchers developed do not just sense and filter at a fast rate, they also compute without needing a power supply.
"There's no distinction between hardware and software in nature; it's all interconnected," Arrieta said. "A sensor is meant to interpret data, as well as collect and filter it."
The artificial mechanosensors that they developed are capable of sensing, filtering and computing at a very fast rate because they are stiff. The sensor material is made to change shape easily and in a fast pace when activated by an external force.
When the shape changes, it makes conductive particles within the material move closer to each other and allows electricity to flow through the sensor and send a signal. The signal informs how the autonomous system should respond.
"With the help of machine learning algorithms, we could train these sensors to function autonomously with minimum energy consumption," Arrieta said. "There are also no barriers to manufacturing these sensors to be in a variety of sizes."
