Damped Least Squares
Damped least squares is a classic means of suppressing jitter in inverse kinematics. By introducing a damping factor into the solution, it sacrifices some end-effector accuracy in exchange for numerical stability, avoiding explosive joint velocities near singular configurations.
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Damped Least Squares (DLS) suppresses IK jitter by introducing a damping factor during solving; the larger the damping factor, the smoother the motion but the larger the tracking error, and the smaller it is, the more precise but the more prone to jitter.
For postures close to singular configurations, pure pseudo-inverse will output huge joint velocities, and adding Damped Least Squares (DLS) can significantly suppress jitter.
DLS and clamping are often used together: first use DLS to ensure numerical stability, then use clamping as a fallback to prevent extreme cases.
All Facts (3)
Damped Least Squares (DLS) suppresses IK jitter by introducing a damping factor during solving; the larger the damping factor, the smoother the motion but the larger the tracking error, and the smaller it is, the more precise but the more prone to jitter.
50%UnverifiedFor postures close to singular configurations, pure pseudo-inverse will output huge joint velocities, and adding Damped Least Squares (DLS) can significantly suppress jitter.
50%UnverifiedDLS and clamping are often used together: first use DLS to ensure numerical stability, then use clamping as a fallback to prevent extreme cases.
50%