Biological Cybernetics
Performance of optical flow techniques
International Journal of Computer Vision
NPSNET: flight simulation dynamic modeling using quaternions
Presence: Teleoperators and Virtual Environments
Flying Fast and Low Among Obstacles: Methodology and Experiments
International Journal of Robotics Research
Vision-based terrain following for an unmanned rotorcraft
Journal of Field Robotics
Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles
Robotics and Autonomous Systems
Advances in Unmanned Aerial Vehicles: State of the Art and the Road to Autonomy
Advances in Unmanned Aerial Vehicles: State of the Art and the Road to Autonomy
A minimalist control strategy for small UAVs
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fly-inspired visual steering of an ultralight indoor aircraft
IEEE Transactions on Robotics
IEEE Spectrum
IEEE Transactions on Robotics
Survey of Motion Planning Literature in the Presence of Uncertainty: Considerations for UAV Guidance
Journal of Intelligent and Robotic Systems
Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems
Journal of Field Robotics
A 3D Collision Avoidance Strategy for UAVs in a Non-Cooperative Environment
Journal of Intelligent and Robotic Systems
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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 6-degree-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 environment monitoring that may require near-obstacle flight in urban areas or mountainous environments. OptiPilot instead uses optic flow to estimate proximity of obstacles and avoid them.Our approach takes advantage of the fact that, for most platforms in translational flight (as opposed to near-hover flight), the translatory motion is essentially aligned with the aircraft main axis. This property allows us to directly interpret optic flow measurements as proximity indications. We take inspiration from neural and behavioural strategies of flying insects to propose a simple mapping of optic flow measurements into control signals that requires only a lightweight and power-efficient sensor suite and minimal processing power.In this paper, we first describe results obtained in simulation before presenting the implementation of optiPilot on a real flying platform equipped only with lightweight and inexpensive optic computer mouse sensors, MEMS rate gyroscopes and a pressure-based airspeed sensor. We show that the proposed control strategy not only allows collision-free flight in the vicinity of obstacles, but is also able to stabilise both attitude and altitude over flat terrain. These results shed new light on flight control by suggesting that the complex sensors and processing required for 6 degree-of-freedom state estimation may not be necessary for autonomous flight and pave the way toward the integration of autonomy into current and upcoming gram-scale flying platforms.