AutoRef honors 2019: Difference between revisions
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<font size=" | <font size="8"> '''AutoRef Honors 2019/20''' </font> | ||
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=Introduction= | |||
[[File:CF_on_laptop.jpg|right|300px|]] | |||
This wiki is the documentation of work delivered by the AutoRef Honors students from the High Tech Systems track in the academic year 2019/2020. | |||
The goal of this project is to develop an autonomous robot capable of refereeing a robot football play. Such a system can be of benefit by eliminating human error and by using factual data from more sources to make better-evaluated decisions. For this project we have decided to use a drone (quadcopter) as a robot. Most drones are fast and they can change altitude easily, this agility enables a drone to quickly move to a position with a good view, this is a large advantage for a referee. Robot soccer is played on fields of different sizes, and a system using a drone is scalable, whereas for instance a camera on a rail next to a field would not be so scalable. Another reason for using a drone is that it is easy to carry around and it is a small object to work on. | |||
We made the project goal more specific into the following: | |||
''''' "Autonomously assist a football referee in a 2 versus 2 robot soccer match using a drone by enforcing three main rules: out of bounds, free kick, and goal."''''' | |||
A large obstacle we faced during the project was that the university had to close due to the Covid-19 virus outbreak from March 2020 until the end of the project year. The effects on this project are that the team has not been able to test hardware on the university or work together physically. Considering these changes the team has decided to move our system to a simulation environment, and the work on the hardware has not been finalized. | |||
=Team= | |||
This project was made by the following Honors student in the academic year 2019/2020: | |||
*Alvaro Gonzalez | |||
*Jake Rap | |||
*Wolff Voss | |||
=References= | |||
Rosebrock, A. (2015). Ball Tracking with OpenCV - PyImageSearch. Retrieved 24 May 2020, from https://www.pyimagesearch.com/2015/09/14/ball-tracking-with-opencv/ | |||
Latest revision as of 19:00, 24 May 2020
AutoRef Honors 2019/20
Introduction
This wiki is the documentation of work delivered by the AutoRef Honors students from the High Tech Systems track in the academic year 2019/2020.
The goal of this project is to develop an autonomous robot capable of refereeing a robot football play. Such a system can be of benefit by eliminating human error and by using factual data from more sources to make better-evaluated decisions. For this project we have decided to use a drone (quadcopter) as a robot. Most drones are fast and they can change altitude easily, this agility enables a drone to quickly move to a position with a good view, this is a large advantage for a referee. Robot soccer is played on fields of different sizes, and a system using a drone is scalable, whereas for instance a camera on a rail next to a field would not be so scalable. Another reason for using a drone is that it is easy to carry around and it is a small object to work on.
We made the project goal more specific into the following:
"Autonomously assist a football referee in a 2 versus 2 robot soccer match using a drone by enforcing three main rules: out of bounds, free kick, and goal."
A large obstacle we faced during the project was that the university had to close due to the Covid-19 virus outbreak from March 2020 until the end of the project year. The effects on this project are that the team has not been able to test hardware on the university or work together physically. Considering these changes the team has decided to move our system to a simulation environment, and the work on the hardware has not been finalized.
Team
This project was made by the following Honors student in the academic year 2019/2020:
- Alvaro Gonzalez
- Jake Rap
- Wolff Voss
References
Rosebrock, A. (2015). Ball Tracking with OpenCV - PyImageSearch. Retrieved 24 May 2020, from https://www.pyimagesearch.com/2015/09/14/ball-tracking-with-opencv/