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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.
|Titel||2022 American Control Conference (ACC)|
|Status||Udgivet - 2022|
|Begivenhed||2022 American Control Conference, ACC 2022 - Atlanta, USA|
Varighed: 8. jun. 2022 → 10. jun. 2022
|Konference||2022 American Control Conference, ACC 2022|
|Periode||08/06/2022 → 10/06/2022|
|Sponsor||Boeing, et al., General Motors Co., MathWorks, Mitsubishi Electric Research Laboratory ((MERL), Quanser|
|Navn||Proceedings of the American Control Conference|
Bibliografisk noteFunding Information:
*This work was supported by the PIRAT project, funded by Innovation Fund Denmark, grant number 9069-00046B.
© 2022 American Automatic Control Council.