The behavior and interplay of two types of neurons in the brain helps give humans and other animals an uncanny ability to navigate by building a mental map of their surroundings. Now one robot has been given a similar cluster of virtual cells to help it find its own way around.
Researchers in Singapore simulated two types of cells known to be used for navigation in the brain — so-called “place” and “grid” cells — and showed they could enable a small-wheeled robot to find its way around. Rather than simulate the cells physically, they created a simple two-dimensional model of the cells in software. The work was led by Haizhou Li, a professor at the Agency for Science, Technology and Research (A*STAR).
“Artificial grid cells could provide an adaptive and robust mapping and navigation system,” Li wrote in an e-mail coauthored with Huajin Tang, a research scientist at A*STAR, and Yuan Miaolong, a graduate student and first author on a paper about the work. “Humans and animals have an instinctual ability to navigate freely and deliberately in an environment rather effortlessly.”
The work is significant because it shows the potential for having machines mimic more complex activity in the brain. Roboticists increasingly use artificial neural networks to train robots to perform tasks such as object recognition and grasping, but these networks do not faithfully reflect the complexity and subtlety of a real biological brain.
“Neural networks are actually very loosely inspired by the brain,” says Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence in Seattle. “They are distributed computing elements, but they’re very simple as compared with neurons; the connections are extremely simple as compared with a synapse.” He says this new development that takes inspiration from the brain “seems like good work.” (Read more from “This Robot Uses Artificial Brain Cells to Navigate Like a Human” HERE)