Robot bat finds insects in darkness with 98% accuracy, mirroring bats

Scientists from the Smithsonian Tropical Research Institute, University of Cincinnati, and University of Antwerp investigated how big-eared bats (Micronycteris microtis) detect silent insects on leaves at night using echolocation. Building on prior behavioral studies, they hypothesized that bats exploit the acoustic properties of leaves: smooth, empty leaves reflect echolocation calls away, producing weak echoes, while insects on leaves scatter sound in multiple directions, creating distinctive echoes. However, precisely measuring leaf orientation to find prey seemed impractical for bats. Instead, the researchers proposed that bats rely on the steadiness of echoes over time rather than detailed spatial mapping. To test this, the team created a robot equipped with ultrasonic sensors mimicking bat echolocation. The robot scanned an array of cardboard leaves, one holding a fake insect, without measuring leaf size or angle. It successfully identified prey-occupied leaves with 98% accuracy and had a low false detection rate (18%) on empty leaves. The findings confirmed that bats detect prey by