Aerodynamic imaging by mosquitoes inspires a surface detector for autonomous flying vehicles

Some flying animals use active sense 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 this behavior is mediated by perceiving modulations of their self-induced airflow patterns as they enter ground or wall effect. We use 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 using a quadcopter with a sensory system inspired by the mosquito. Such low power sensing systems have major potential for future, safer, rotorcraft control systems.