How AI-powered echolocation is giving small drones night vision

To help small aerial robots navigate in the dark and other low-visibility environments, my colleagues and I developed an ultrasound-based perception system inspired by bat echolocation. Current robots rely heavily on cameras or light detection and ranging, known as lidar, or both. But these sensors fail in visually challenging conditions, such as smoke, fog, dust, snow, or complete darkness. I’m a scientific engineer who develops bio-inspired microrobots. To solve this challenge, my research team looked at nature’s experts at navigating in poor visibility: bats. They thrive in dark, damp, and dusty caves and can detect obstacles as thin as a human hair using echolocation while weighing as little as two paper clips. They emit sound waves and listen to weak echoes reflected from objects. However, enabling this sensing on aerial robots is extremely challenging because propellers generate a lot of noise. It is a bit like trying to listen to your friend while a jet engine is taking off next