Hybrid Force Motion Control with Estimated Surface Normal for Manufacturing Applications

Ehsan Nasiri, Long Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a hybrid force-motion framework that utilizes real-time surface normal updates. The surface normal is estimated via a novel method that leverages force sensing measurements and velocity commands to compensate the friction bias. This approach is critical for robust execution of precision force-controlled tasks in manufacturing, such as thermoplastic tape replacement that traces surfaces or paths on a workpiece subject to uncertainties deviated from the model. We formulated the proposed method and implemented the framework in ROS2 environment. The approach was validated using kinematic simulations and a hardware platform. Specifically, we demonstrated the approach on a 7-DoF manipulator equipped with a force/torque sensor at the end-effector.

Original languageEnglish
Title of host publication2024 21st International Conference on Ubiquitous Robots, UR 2024
Pages125-132
Number of pages8
ISBN (Electronic)9798350361070
DOIs
StatePublished - 2024
Event21st International Conference on Ubiquitous Robots, UR 2024 - New York, United States
Duration: 24 Jun 202427 Jun 2024

Publication series

Name2024 21st International Conference on Ubiquitous Robots, UR 2024

Conference

Conference21st International Conference on Ubiquitous Robots, UR 2024
Country/TerritoryUnited States
CityNew York
Period24/06/2427/06/24

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