A team led by Worcester Polytechnic Institute (WPI) researcher Nitin J. Sanket has shown that ultrasound sensors and a form of artificial intelligence (AI) can enable palm-sized aerial robots to navigate with limited power and computation through fog, smoke, and other challenging conditions during search-and-rescue operations.
The advance, inspired by bats and published in the journal Science Robotics, suggests that ultrasound may be an alternative to existing navigation technologies that add weight and cost to a drone or falter in poor conditions.
“Bats that weigh less than two paper clips can accurately navigate in dark, damp, and dusty caves by sending out short chirps and listening to the weak echoes with a limited number of neurons,” said Sanket, assistant professor in the Department of Robotics Engineering. “By creating an ultrasound-based system that needs just two tiny sensors and little computation, we can open up opportunities for small aerial robots to perceive their surroundings, make decisions, and independently operate longer in cluttered, hazardous places where current aerial robots struggle.”
Sanket’s research focuses on robotics inspired by nature, such as bees and bats. The work featured in Science Robotics was supported by a grant from the National Science Foundation.
Autonomous aerial robots typically use sensors, controllers, cameras, a power source, and sophisticated algorithms to perceive their surroundings and make navigational decisions.
Some robots collect information about a landscape by analyzing radio waves or light pulses. However, technology based on lidar—light detection and ranging—and radar are heavy, power intensive, and costly. Darkness, poor weather, and noise can interfere with light-based perception systems. Sound from propellers adds complexity to an aerial robot’s calculations that aim to decipher useful echoes from propeller noise. Analyzing data requires a robot’s time and energy.
