SH
S. Hossain
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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. ...
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. ...
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.
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.
Although the demand for wireless communication continuous to grow, the number of frequencies available in traditional data transmission is limited. Visible Light Communication (VLC) is a promising alternative communication method proven to work on high-end devices. However, large-scale adoption requires VLC to also work on everyday machines. Yet, no published research has proven effectiveness on low-end devices. This work describes how a communication system using light can be implement on a low-end smart phone, using a LED as a transmitter. Furthermore, it compares two methods of (de)modulation, namely On-Off Keying and Differential Manchester Code. Evaluation results demonstrate a working system with a maximum bit-rate of approximately 3000bps.
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Although the demand for wireless communication continuous to grow, the number of frequencies available in traditional data transmission is limited. Visible Light Communication (VLC) is a promising alternative communication method proven to work on high-end devices. However, large-scale adoption requires VLC to also work on everyday machines. Yet, no published research has proven effectiveness on low-end devices. This work describes how a communication system using light can be implement on a low-end smart phone, using a LED as a transmitter. Furthermore, it compares two methods of (de)modulation, namely On-Off Keying and Differential Manchester Code. Evaluation results demonstrate a working system with a maximum bit-rate of approximately 3000bps.