- 2 FIRST Tech Challenge (FTC) teams
- 3 FIRST Lego League (FLL) teams
We are currently gearing up for the 2017-18 season and would love to have you join us. You must be enrolled as a member of S.A.Y. Detroit Play in order to qualify for one of our 5 teams in the robotics program. If you wish to join a team, please download this consent form or simply stop by the center for one. Your team coach/mentor will then register you.
In the FIRST Tech Challenge, teams of at least 10 middle and high school-aged students (grades 7-12) are challenged to design, build, program, and operate a robot to play a floor game against other teams’ creations in an alliance format. Students develop STEM skills and practice engineering principles, while learning the value of hard work, innovation, and collaboration. Participants on FTC teams also have access to college scholarships.
Our FTC teams meet on Mondays and Wednesday from 6 - 7:30pm. Many thanks to coach James Teasley from Ford, and mentor Thomas Kyer from Ford for supporting our FTC Teams.
Nov 18-19, 2016:Frog Force Frenzy FTC Qualifier in Novi, MI
Steam Team Rank: 13/34
Robot Warriors Rank: 19/34
Guided by two or more adult coaches, FIRST LEGO League teams (up to 10 members, grades 4-8) research a real-world problem such as food safety, recycling, energy, etc., and are challenged to develop a solution. They also must design, build, and program a robot using LEGO MINDSTORMS®, then compete on a table-top playing field.
Our FLL teams meet on Tuesdays and Thursdays from 6 - 7:30pm. Many thanks to our team mentors from Dow, Cooper Standard and Ford: Pascal Roy, Sabrina Walker-Crump, Darryl Foster, Tom Catton, and Michael Riffenburg.
Nov 12, 2016: Michigan Science Center Regional Qualifier
24 teams from 14 cities in southeast Michigan took part. Learn more.
- Identify a problem that happens when animals and humans interact.
- Design an innovative solution that makes the interaction better for animals, people, or both.
- Share their problem and solution with others.
- Build, test, and program an autonomous robot to solve missions on an obstacle course.