Attitude Stabilization of a Biologically Inspired Robotic Housefly via Dynamic Multimodal Attitude Estimation

In this paper, we study sensor fusion for the attitude stabilization of Micro Aerial Vehicles (MAVs), in particular mechanical flying insects. Following a geometric approach, a dynamic observer is proposed which estimates attitude based on kinematic data available from different and redundant bio-inspired sensors such as halteres, ocelli, gravitometers, magnetic compass and light polarization compass. In particular, the traditional structure of complementary filters, suitable for multiple sensor fusion, is specialized to the Lie group of rigid body rotations SO(3). The filter performance based on a 3-axis accelerometer and a 3-axis gyroscope is experimentally tested on a 2 degreesof-freedom support showing its effectiveness. Finally, attitude stabilization is proposed based on a feedback scheme with dynamic estimation of the state, namely the orientation and the angular velocity. Almost-global stability of the proposed controller in the case of dynamic state estimation is demonstrated via the separation principle, and realistic numerical simulations with noisy sensors and external disturbances are provided to validate the proposed control scheme. keywords: attitude control on SO(3), separation principle, geometric control, complementary filtering, biologically inspired robots.