While collision avoidance and flight stability are generally a micro air vehicle's (MAVs) highest priority, many map-based path planning algorithms focus on path optimality, often assuming a static, known environment. For many MAV applications a robust navigation solution requires responding quickly to obstacles in dynamic, tight environments with non-negligible disturbances. This article first outlines the Reactive Obstacle Avoidance Plugin framework as a method for leveraging map-based algorithms while providing low-latency, high-bandwidth response to obstacles. Further, we propose and demonstrate the effectiveness of the Cushioned Extended-Periphery Avoidance (CEPA) algorithm. By representing recent laser scans in the current body-fixed polar coordinate frame, a 360¿¿ lower-bound understanding of the environment is available. With this extended field of view, motion assumptions common in other reactive planners can be relaxed and emergency control effort can be applied in any direction. CEPA is validated in simulation and on hardware in a GPS-denied environment using strictly onboard computation and sensing.
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