Online Adaptive Identification and Switching of Soft Contact Model Based on ART-II Method - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2022

Online Adaptive Identification and Switching of Soft Contact Model Based on ART-II Method

Abstract

In order to obtain a high-precision contact model that can properly describe the target soft tissue, this paper proposes a hybrid soft contact model based on a clustering algorithm ART-II, which selects the most suitable soft contact model according to the surgical environment. The least-square method is used to identify the parameters of the model online. In the experiments, different parts of animal tissues were used as the experimental objects. The hybrid model was used to identify and switch for the most appropriate soft contact model when dealing with a certain type of animal tissue. The performance of the hybrid model on force estimation was compared with several individual soft contact models. The results showed that the estimated/reconstructed force of the hybrid model was closer to the ground truth measured by the force sensor. In addition, a new reference soft contact model has been purposely added online to verify the expandability of the hybrid model.
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Dates and versions

lirmm-03859350 , version 1 (18-11-2022)

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Cite

Yi Liu, Di Wu, Fengtao Han, Jing Guo, Zhaoshui He, et al.. Online Adaptive Identification and Switching of Soft Contact Model Based on ART-II Method. ICRA 2022 - IEEE International Conference on Robotics and Automation, May 2022, Philadelphia, United States. pp.8855-8861, ⟨10.1109/ICRA46639.2022.9811740⟩. ⟨lirmm-03859350⟩
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