Gruev's bioinspired camera could help autonomous cars see better
ECE ILLINOIS Professor Viktor Gruev led a team of researchers to develop a new camera that could significantly improve the ability of self-driving cars to identify hazards in challenging imaging conditions. By detecting polarization and featuring a dynamic range that is about 10,000 times higher than today's commercial cameras, these new cameras are able to see better in hazardous driving conditions including "the transition from a dark tunnel into bright sunlight or during hazy or foggy conditions" according to The Optical Society.
In Optica, The Optical Society's journal for high impact research, Viktor and his team described how this new camera could "detect hazards, other cars and people three times farther away" than the color cameras that are used on cars today. "In a recent crash involving a self-driving car, the car failed to detect a semi-truck because its color and light intensity blended with that of the sky in the background," said Gruev. "Our camera can solve this problem because its high dynamic range makes it easier to detect objects that are similar to the background and the polarization of a truck is different than that of the sky."
Furthermore, the researchers are exploring other applications of these cameras including the detection of cancer cells, which exhibit a different light polarization than normal tissue and to improve upon ocean exploration.
Gruev's camera is inspired by mantis shrimp which have a logarithmic response to light intensity. The shrimps are "sensitive to a high range of light intensities" so the researchers modeled their cameras after the logarithmic dynamic range of the shrimps by using an unorthodox forward bias mode rather than the traditional reverse bias mode.