Aerodynamic imaging by mosquitoes inspires a surface detector for autonomous flying vehicles
Toshiyuki Nakata, Nathan Phillips, Patrício Simões, Ian J. Russell, Jorn A. Cheney, Simon M. Walker, Richard J. Bomphrey
Abstract
Some flying animals use active sensing to perceive and avoid obstacles. Nocturnal mosquitoes exhibit a behavioral response to divert away from surfaces when vision is unavailable, indicating a short-range, mechanosensory collision-avoidance mechanism. We suggest that this behavior is mediated by perceiving modulations of their self-induced airflow patterns as they enter a ground or wall effect. We used computational fluid dynamics simulations of low-altitude and near-wall flights based on in vivo high-speed kinematic measurements to quantify changes in the self-generated pressure and velocity cues at the sensitive mechanosensory antennae. We validated the principle that encoding aerodynamic information can enable collision avoidance by developing a quadcopter with a sensory system inspired by the mosquito. Such low-power sensing systems have major potential for future use in safer rotorcraft control systems.