Document Type

Conference Paper

Publication Date

2025

DOI

10.1016/j.ifacol.2025.12.368

Publication Title

IFAC PapersOnLine

Volume

59

Issue

30

Pages

988-993

Conference Name

5th Conference on Modeling, Estimation and Control MECC 2025, October 5-8, 2025, Pittsburgh, United States

Abstract

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 realtime. 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.

Rights

© 2025 The Authors.

This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License.

Original Publication Citation

Gholampour, H., Slightam, J. E., & Beaver, L. E. (2025). Mass-adaptive admittance control for robotic manipulators. IFAC PapersOnLine, 59(30), 988-993. https://doi.org/10.1016/j.ifacol.2025.12.368

ORCID

0009-0001-9566-9326 (Dadaei), 0000-0002-9770-2740 (Beaver)

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