Antoine Beyeler

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This paper presents a novel control strategy, which we call optiPilot, for autonomous flight in the vicinity of obstacles. Most existing autopilots rely on a complete 6degree-of-freedom state estimation using a GPS and an Inertial Measurement Unit (IMU) and are unable to detect and avoid obstacles. This is a limitation for missions such as surveillance and(More)
The significant increase in the available computational power that took place in recent decades has been accompanied by a growing interest in the application of the evolutionary approach to the synthesis of many kinds of systems and, in particular, to the synthesis of systems like analog electronic circuits, neural networks, and, more generally, autonomous(More)
Fully autonomous control of ultra-light indoor airplanes has not yet been achieved because of the strong limitations on the kind of sensors that can be embedded making 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 the(More)
We aim at developing ultralight autonomous microflyers capable of freely flying within houses or small built environments while avoiding collisions. Our latest prototype is a fixed-wing aircraft weighing a mere 10 g, flying around 1.5 m/s and carrying the necessary electronics for airspeed regulation and lateral collision avoidance. This microflyer is(More)
There are not yet autonomous flying robots capable of manoeuvring in small cluttered environments as insects do. Encouraged by this observation, this thesis presents the development of ultra-light flying robots and control systems going one step toward fully autonomous indoor aerial navigation. The substantial weight and energy constraints imposed by this(More)
Because of their ability to naturally float in the air, indoor airships (often called blimps) constitute an appealing platform for research in aerial robotics. However, when confronted to long lasting experiments such as those involving learning or evolutionary techniques, blimps present the disadvantage that they cannot be linked to external power sources(More)
Take-off and landing manoeuvres are critical for MAVs because GPS-based autopilots usually do not perceive distance to the ground or other potential obstacles. In addition, attitude estimates based on inertial sensors are often perturbed by the strong accelerations occurring during launch. This paper shows how our previously developed control strategy,(More)
The ability to fly at low altitude while actively avoiding collisions with the terrain and objects such as trees and buildings is a great challenge for small unmanned aircraft. This paper builds on top of a control strategy called optiPilot whereby a series of optic-flow detectors pointed at divergent viewing directions around the aircraft main axis are(More)
This paper presents an affordable, fully automated and accurate mapping solutions based on ultra-light UAV imagery. Several datasets are analysed and their accuracy is estimated. We show that the accuracy highly depends on the ground resolution (flying height) of the input imagery. When chosen appropriately this mapping solution can compete with traditional(More)