Towards Contact Point and Surface Normal Estimation for Control of Flexible Tool

Christoffer Sloth*, Aljaz Kramberger, Emil Lykke Diget, Inigo Iturrate

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

In this paper, we present contact point and surface normal estimators for robotic applications with flexible tools. The estimators rely on state information of a flexible tool model; this information is obtained from an unknown input observer. The observer uses force and torque measurements at the root of the flexible tool to estimate the deflection of the tool although the force applied to the tip of the tool is unknown. The flexible tool is modeled with a finite element approximation of an Euler-Bernoulli beam model including contact forces between the flexible tool tip and the environment.The unknown input observer provides estimates of the contact point between the flexible tool and the rigid environment in addition to the contact force. This information is subsequently used to estimate a surface normal of the environment. The estimators can be deployed together with an adaptive parallel position/force controller to ensure tracking of position and force references for the tip of a flexible tool.The proposed estimation algorithm is verified in simulation and validated in real robot experiments. The method enables accurate force and position tracking in addition to adaptation to the surface geometry.

Original languageEnglish
Title of host publication2022 American Control Conference (ACC)
PublisherIEEE
Publication date2022
Pages500-505
ISBN (Electronic)9781665451963
DOIs
Publication statusPublished - 2022
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: 8. Jun 202210. Jun 2022

Conference

Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States
CityAtlanta
Period08/06/202210/06/2022
SponsorBoeing, et al., General Motors Co., MathWorks, Mitsubishi Electric Research Laboratory ((MERL), Quanser
SeriesProceedings of the American Control Conference
Volume2022-June
ISSN0743-1619

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  • PIRAT

    Sloth, C.

    01/10/201901/10/2023

    Project: Research

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