Flight control and collision avoidance for quadcopter and flapping wing MAVs using only optical flow

Abstract

Both quadcopter Micro Aerial Vehicles (MAVs) and Flapping Wing MAVs (FWMAVs) are constrained in Size, Weight and Processing power (SWaP) in order to achieve flight tasks that include attitude and velocity stabilisation, as well as obstacle avoidance.
Conventional sensory and control approaches, such as those relying on inertial, visual and Global Positioning System (GPS) sensors, can fulfil these tasks using sensor fusion. However such approaches do not score well in terms of SWaP criteria.
Very simple proportional feedback control laws using single optical flow vectors from very basic high frame-rate low-resolution cameras provide a promising path to achieve aforementioned tasks.
This thesis shows that in theory these control laws are well suited for stabilising a FWMAV, and could be used for a high-drag adapted quadcopter MAV within bounds. Simulations confirm these findings and illustrate robustness to noise and additional emergent behaviour such as sideways wall avoidance and trajectory following, however simulations also show that disparity between walls can lead to unintended rotational behaviour during vertical translation.
The system is tested in experiment on a quadcopter-like setup with onboard processing, using only ADNS 9800 computer mouse optical flow sensors for flight control. Results show that the system behaves similarly to simulation, however the sensory configuration used is highly dependent on texture in environment and light conditions.
For future work it is recommended to investigate optical flow sensors in more detail to obtain reliable output on a vibrating platform (such as a FWMAV) in a broader range of texture and light conditions. Preliminary results from theory, simulation and experiment indicate that the addition of derivative feedback could strongly enhance performance on a quadcopter MAV and remove the requirement for high drag.