Professor Barani Raman at Washington University in St.Louis has developed a printed circuit board (PCB) capable of measuring the brain activity of locusts with the use of a micro-electrode and processor. With the use of this PCB,they are developing cyborg locusts capable of sensing the presence of explosives to be used in homeland security applications. Before they can be used in real world applications a way to guide and navigate the locusts remotely must be developed.
By studying the biological control systems of locusts, Professor Raman’s PCB may be used to control the locust as well as measure its brain activity. In order to study the biological control system of the locust, a way to repeatedly guide the locust in flight must be developed.
This project was initially designed to provide Dr. Raman and his research with a drone capable of stable, repeatable flights for experiments. The project was defined to feature a platform to carry the locust and sensors to collect brain signals from the locust when subject to positive and negative stimulus via odor plumes along various flight paths. This is still the goal, however due to the COVID-19 pandemic many of the in-lab objectives were moved to simulations and data collection will have to be conducted beyond the deadline of this project by Dr. Raman’s team.
This project will assist assist Dr. Barani Raman’s research by developing a drone capable of carrying a locust equipped with his PCB through repeatable, pre-planned flight paths. Initially, this was to include a platform to carry the locust on drone, a feedback based control system to control the drone, live feedback from the PCB in-stalled into the locust, and live position feedback via an OptiTrack system.
Due to the Covid-19 pandemic, some objectives were no longer achievable. The lab containing the drones and OptiTrack system is no longer available. Consequently,the project will instead provide the ability to track the drones position with the OptiTrack system, a control system capable of flying the drone through a pre-planned flight path and a simulation confirming the stability, and path of the drone with currently modeled dynamics.