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@vibetimezreviews: Stock turn signals don’t cut it anymore 💡 These LED switchback turn signal bulbs go white while driving → amber when signaling for a clean, modern look. Super bright, 360° output, no hyper-flash, and CanBus ready — plug & play upgrade in minutes. ✔️ White DRL + Amber turn ✔️ No dash errors ✔️ No glare ✔️ Low power draw ✔️ Instant upgrade #CarTok #TruckTok #AutoTok #CarMods #TruckMods

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Build a complete wheel-encoder lab in one HTML file. Follow the full readable source, connect Start/Pause/Reset, animate a wheel, estimate distance from decoded counts and compare normal rolling with simplified slip. Pause the numbered source pages to copy the code; gutter arrows mean the same source line continues. This is an original virtual educational model and model-driven animation, not a browser recording, physical robot test, safety certification or verified NewBrain capability. The 0.10 m wheel and 240 decoded counts per WHEEL revolution are invented lesson settings. One count represents pi × 0.10 / 240 approximately 1.309 mm of estimated wheel travel. Real pulse conventions and gearing differ. The model changes commanded speed instantly; it does not simulate real braking. Its fixed 60% ground-travel multiplier illustrates slip rather than modelling tyre physics. At 60 updates/s, the one-metre replay ends at 766 counts, approximately 1.002692 m estimated travel. The slip replay has the same count but only 0.602 m ground travel. Browser update timing can produce different endpoints. Robert's authorized narration was synthesized locally with AI. Complete captions and original animation. No private voice references are shared. Kira Labs is my own project: https://kiralabs.org Technical references: https://www.pololu.com/docs/0J86/6.4 https://docs.wpilib.org/en/stable/docs/software/hardware-apis/sensors/encoders-software.html https://developer.mozilla.org/en-US/docs/Web/API/Window/requestAnimationFrame #KiraLabs #Robotics #LearnToCode #JavaScript #WheelEncoder
Build a complete wheel-encoder lab in one HTML file. Follow the full readable source, connect Start/Pause/Reset, animate a wheel, estimate distance from decoded counts and compare normal rolling with simplified slip. Pause the numbered source pages to copy the code; gutter arrows mean the same source line continues. This is an original virtual educational model and model-driven animation, not a browser recording, physical robot test, safety certification or verified NewBrain capability. The 0.10 m wheel and 240 decoded counts per WHEEL revolution are invented lesson settings. One count represents pi × 0.10 / 240 approximately 1.309 mm of estimated wheel travel. Real pulse conventions and gearing differ. The model changes commanded speed instantly; it does not simulate real braking. Its fixed 60% ground-travel multiplier illustrates slip rather than modelling tyre physics. At 60 updates/s, the one-metre replay ends at 766 counts, approximately 1.002692 m estimated travel. The slip replay has the same count but only 0.602 m ground travel. Browser update timing can produce different endpoints. Robert's authorized narration was synthesized locally with AI. Complete captions and original animation. No private voice references are shared. Kira Labs is my own project: https://kiralabs.org Technical references: https://www.pololu.com/docs/0J86/6.4 https://docs.wpilib.org/en/stable/docs/software/hardware-apis/sensors/encoders-software.html https://developer.mozilla.org/en-US/docs/Web/API/Window/requestAnimationFrame #KiraLabs #Robotics #LearnToCode #JavaScript #WheelEncoder
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