Nanogenerator based self-powered motion monitoring for flapping wings of bio-inspired flying robots

Abstract

Under the constraints of weight and power, achieving airborne monitoring of wings' flexible motion toward bio-inspired flying robots is an arduous challenge. Herein, we present a self-powered motion monitoring method based on nanogenerators to tackle this issue. First, a locally adaptable integration structure of triboelectric nanogenerator (TENG) integrated wings is proposed for the design of airborne devices. Second, a theoretical output model is developed to dynamically monitor the flapping motion of TENG-integrated wings. The proposed approach is a multi-target monitoring technique that enables the sensing of parameters, such as the flapping frequency and the flapping angles with stability. After validation, the monitoring error of the wing plane's pitch angle affected by device stability is less than 0.7°. Likewise, the maximum observed error rate for flapping frequency monitoring is about 0.1%. This technique will further enhance the intelligent airborne wing state perception for bio-inspired flying robots.