3D Vision-based Navigation for Indoor Microflyers
Fully autonomous control of ultra-light indoor airplanes has not yet been achieved because the strong limitations on the kind of sensors that can be embedded make it difficult to obtain good estimations of altitude. We propose to revisit altitude control by considering it as an obstacle avoidance problem and introduce a novel control scheme where ground and ceiling is avoided based on translatory optic flow, in way similar to existing vision- based wall avoidance strategies. We show that this strategy is successful at controlling a simulated microflyer without any explicit altitude estimation and using only simple sensors and processing that have already been embedded in an existing 10-gram microflyer. This result is thus a significant step toward autonomous control of indoor flying robots.