MicroCart (Microprocessor Controlled Aerial Robotics Team)
Introduction
Microprocessor Controlled Aerial Robotics Team or MicroCART project is centered around the development of a quadcopter and tracking system. This project has been in development since 1998 and the current system has been passed down since 2006. The project aims to create a stable and easy to use platform for researching control theory and to showcase the skills that a student in the ECpE department can gain throughout their time at Iowa State by creating an impressive demo that the quad can perform. The quadcopter flies primarily in the Distributed Sensing and Decision Making Laboratory within a twelve camera infrared tracking system.
Goals
1. Implementation of Second Drone
We are going to make an exact copy of the current drone platform from the previous year. Most of the work done on this portion will be in the form of research on the existing system. In order to make another platform we will need to research the existing documentation. We are making this deliverable, because we need to have one stable platform to demo our solution to people and one for a senior design team to do development on. This deliverable should be completed by October 25th.
2. Swarm Flight of Crazy Flies
After we have a second drone, we will hopefully have access to several crazy flies. We can use these platforms to test out extending our GCS software to multiple platforms. This is an intermediate deliverable. We will use this deliverable to get experience with programming swarm flight with inexpensive platforms and move on to our permanent solution for swarm flight. We should have this portion completed by November 1st.
3. Swarm Flight of large drones
After we have experience with swarm flight on the crazy flies and have the second drone built, we will work on having two drones operate simultaneously. This deliverable relates to our client need of demoing to students and faculty. Showing multiple vehicles operating simultaneously is more impressive than just a single vehicle. This showcases the usefulness of skills obtained with an ECPE degree. Controls students also will want to test control algorithms with multiple platforms interacting. This should be done by December 2nd.
4. Addition of Linux to Second Core
After we have both drones fully implemented and functioning properly, we will need to add new features to our board to showcase skills that we have learned from our degree. One of the features we plan on adding is Linux to the second core. The Zybo board has two ARM cores. We will install Linux on the second core and this will give researchers and future project teams greater flexibility to control our platform. We can also use it to view the value of a degree. We can install an image detection library like OpenCV and a camera on Linux and use image detection to give control commands to the drone. This will be done at some point during the second semester of this course.
5. Modular Control Algorithm Swapping on the Drone.
Another feature we plan on implementing is the modularity on control algorithms. Currently, the drone control program runs a PID based position correction algorithm. It measures the differences between the set points and the actual position of the drone that is captured.
6. More Interactive and Comprehensive UI
When talking with the current users of our project, we found that it would be helpful to create a more interactive element for the data from the quadcopter, camera system and ground station. We will do this by adding new CTEs, sliders and graphs to help visualize the input, output and calculated data.