The objective of the 2022 ASEE Robotics Competition, hosted in Minneapolis, Minnesota, was to design and build an autonomous robot that can successfully gather up to 12 legal size (yellow) fish from the three blue lakes on the track and deliver them to either of two fishing stations. The lakes also contain 4 undersized (red) fish which must be left in each lake or returned to one of the lakes. The robots will have a maximum time of 120 seconds in each of their four allotted trials. The robot must begin within an 8” X 12” X 10” high size limit but may expand to any size during a trial. An Exhibit Session will precede the robot trials.

This year the competition shared several similarities with previous competitions. This allowed us to look back on several previous robot designs for inspiration. The 2011 robot had a similar mission to this year's because it involved collecting objects from the field as quickly as possible. We used a similar collection arm design that hits the fish well below their center of gravity and relies on the fish falling onto it. This made for a fast and reliable collection method. We also used a steering design similar to our 2003 robot's. One of the most important things we learned from last year's robot was the benefit of using tight tolerances. This greatly improved the reliability of the robot. We also chose a two wheeled design because we learned last year that four wheeled designs often suffer from excessive chassis flex and must have complex suspension systems to compensate.

This year's competition brought several unique challenges. We had to design a robot that could reliably drive around several lakes of differing diameter. We used two bearings on the side of the robot to run against the edge of each raised lake. This made the robot track the lake edges much more reliably while simplifying programming. We were also required to differentiate between the legal yellow fish and the illegal red fish. As they are a different height, we decided to use an infrared sensor to differentiate the fish based on height. This method was faster and more reliable than using a color sensor. This year also presented several programming challenges and very little code could be reused from previous robots.