A robotic arm executes a sequence of movements. Positional error accumulates with each step. Which strategy best stabilizes the arm's trajectory?

💡 Explanation

Kalman filtering recursively estimates the state of a system by incorporating new measurements, because it minimizes the mean squared error. Therefore, it stabilizes the arm’s trajectory by reducing the accumulation of positional errors, rather than increasing motor torque, which could cause overshoot or instability.

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