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Robotic Obstacle Course Navigation

Using a robotic tugboat my team and I competed with classmates to autonomously navigate through a series of obstacles. An overhead camera was used to track robots for localization, and obstacle avoidance was done using an IR sensor mounted on a servo. For added challenge a region of the map is obscured from the overhead camera.


We competed in three challenges revolving around navigating around buoys in a circular pool. Programmming was done in LabView using an architecture that mimicked the human brain. A forebrain handled high level tasks such as path planning and goal handling.  A midbrain handled tasks such as obstacle avoidance, determining desired direction and velocity, and processing sensor data.  A hindbrain was responsible for collecting sensor data, executing motor and rudder commands, and swiveling the ir sensor to detect obstacles.

Team Size: 3*

Project Duration: 4 weeks

Year Completed: Junior

Key Skills: LabView, Robot Vision, Robot Controls,  Path Planning

*due to certain members' workload conflicts, the effective Team Size was reduced to 3 from the intended 6

 

Due to end of semester scheduling issues, our team was reduced from 6 to 3 members unexpectedly As a result the remaining team, inlcuding myself, pulled double duty. This resulted in some very long nights and had us coding right down to the gaps between heats. Despite this we were able to win all three challenges and recieve the victors award of skipping the lab report! Our secret to success was problem simplificiation. While ever other team attempted to get navigation working at low speeds, then tune it to work at higher speeds, we started at top speed. Our navigation would in fact only work when the robot travelled at top speed. Focusing our efforts this way, and working harder than every other team, gave us the edge we needed to win despite our reduced personpower,

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