Handling objects with unknown or changing masses is a common challenge in
robotics, often leading to errors or instability if the control system cannot
adapt in real-time. In this paper, we present a novel approach that enables a
six-degrees-of-freedom robotic manipulator to reliably follow waypoints while
automatically estimating and compensating for unknown payload weight. Our
method integrates an admittance control framework with a mass estimator,
allowing the robot to dynamically update an excitation force to compensate for
the payload mass. This strategy mitigates end-effector sagging and preserves
stability when handling objects of unknown weights. We experimentally validated
our approach in a challenging pick-and-place task on a shelf with a crossbar,
improved accuracy in reaching waypoints and compliant motion compared to a
baseline admittance-control scheme. By safely accommodating unknown payloads,
our work enhances flexibility in robotic automation and represents a
significant step forward in adaptive control for uncertain environments.

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