Motion detection in the fly is extremely fast with low computational requirements. Inspired from the fly's vision system, we focus on a real-time flight control on a miniquadrotor with fast visual feedback. In this work, an elaborated elementary motion detector (EMD) is utilized to detect local optical flow. Combined with novel receptive field templates, the yaw rate of the quadrotor is estimated through a lookup table established with this bioinspired visual sensor. A closed-loop control system with the feedback of yaw rate estimated by EMD is designed. With the motion of the other degrees of freedom stabilized by a camera tracking system, the yaw-rate of the quadrotor during hovering is controlled based on EMD feedback under real-world scenario. The control performance of the proposed approach is compared with that of conventional approach. The experimental results demonstrate the effectiveness of utilizing EMD for quadrotor control. 1. Introduction Flying insects have tiny brains and mostly possess compound eyes which can get panoramic scene to provide an excellent flying performance. Comparing with state-of-the-art artificial visual sensors, the optics of compound eye provide very low spatial resolution. Nevertheless, the behavior of flying insects is mainly dominated by visual control. They use visual feedback to stabilize flight [1], control flight speed, [2] and measure self-motion [3]. On the other hand, highly accurate real-time stabilization and navigation of unmanned aerial vehicles (UAVs) or microaerial vehicles (MAVs) is becoming a major research interest, as these flying systems have significant value in surveillance, security, search, and rescue missions. Thus, the implementation of a bio-plausible？ computation for visual systems could be an accessible method to replace the traditional image processing algorithms in controlling flying robots such as a quadrotor. Most of early applications using insect-inspired motion detector focus on motion detection tasks rather than velocity estimation. In robotics and automation applications, EMDs are mainly used for a qualitative interpretation of video image sequence, to provide general motion information such as orientation and infront obstacles. In [4], a microflyer with an onboard lightweight camera is developed, which is able to fly indoor while avoiding obstacles by detecting certain changes in optic flow. The recent approach for the navigation in a corridor environment on an autonomous quadrotor by using optical flow integration is shown in [5]. Another example is a tethered optic flow-based
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