Auto-Aiming: Odometry & Vision Integration
Fusing Limelight data with Odometry. How to build a bulletproof goal-tracking system.
Auto-Aiming: Odometry & Vision Integration
How does your robot know where the goal is?
Method 1: Odometry (Dead Reckoning)
- Concept: “I started at (0,0). I moved forward 10 inches. I am at (0,10). The goal is at (0,72). Therefore, I aim at 0 degrees.”
- Pros: Fast (200Hz loop). Always available.
- Cons: Drift. If your wheels slip, your math is wrong forever.
Method 2: Vision (AprilTags/Limelight)
- Concept: Camera sees a tag. Calculates distance and angle.
- Pros: Absolute truth. Corrects for drift.
- Cons: Slow (30Hz). Latency. If the tag is blocked, you are blind.
Method 3: Sensor Fusion (The Winner)
Use Odometry for the high-speed loop.
Use Vision to “reset” or “correct” your Odometry (x,y) position every time you see a tag.
Conclusion
Don’t choose. Fuse. This gives you the speed of odometry with the accuracy of vision.
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