The usage of robots replacing human tasks has become more prevalent. Controlling multiple of these robots can be useful in applications such as disaster response, surveillance and exploration. This form of control is often achieved by using geometric patterns, such as triangles,
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The usage of robots replacing human tasks has become more prevalent. Controlling multiple of these robots can be useful in applications such as disaster response, surveillance and exploration. This form of control is often achieved by using geometric patterns, such as triangles, squares, etc. Drones can employ this concept of formation control to fly and maneuver through environments and obstacles.
In this work a distributed affine formation control algorithm is implemented onto a Crazyflie drones from Bitcraze. Ultra-wideband is used for positioning and communication between the drones. The implementation of the affine formation control algorithm is optimised such that it is only executed when new information is available, to prevent onboard microcontroller from bottlenecking. This resulted in the drones flying in formation successfully with an accuracy of approximately 6.80 cm from its expected position.
Additionally, this algorithm is extended to manage cases where unexpected missing drones could comprise the stability of the formation. The implementation uses the CMSIS library that is optimised for matrix operations. This resulted in the drones flying in formation successfully even in the case of an observation loss with an accuracy of approximately 17.69 cm.
This work not only provides empirical data of experiments with an affine formation control algorithm, but also provides a baseline implementation for future research in the field of affine formation control, which can potentially lead to noise analysis or the application affine formation controls under different circumstances.
