Hardware and software architecture for state estimation on an experimental low-cost small-scaled helicopter

This paper reports the design and testing of an embedded system for a low-cost small scaled helicopter (Benzin Acrobatic from VarioTM with a 1.8 m diameter rotor). The sensors under consideration are an Inertial Measurement Unit (IMU), a GPS, a magnetometer, a barometer and on–off switches serving as take-off and landing detector. Along with one PC board and one micro-controller, they represent a total cost below USD 3000. By contrast to other experiments reported in the literature, the presented work do not rely on any accurate IMU or GPS systems which costs are, separately, largely above the mentioned amount of USD 3000. To compensate the weaknesses of this low cost equipment, efforts focus on designing a robust, dependable and sufficiently embedded system, which exploits an accurate flight dynamics model. This improves the prediction capabilities of an embedded extended Kalman filter that serves for data fusion. The main contribution of this paper is to detail, at the light of a successful reported autonomous hovering flight, the hardware, software architectures and the derivation of the model along with its calibration. Numerous implementation details are presented and the relevance of some modeling hypothesis is discussed.