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Validating Robot Friction Compensation Effects
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Validating Robot Friction Compensation Effects

We validate the effects of friction compensation and acceleration feedforward on a 6-axis collaborative robot through 160 runs of 2x2 experiments. Friction coefficients were tuned using an AI agent (ralph-loop), and validation experiments were conducted with automated scripts. Friction compensation alone achieved 36% improvement (Cohen's d=1.49), accounting for 93% of total improvement.