Object State Estimation Through Robotic Active Interaction for Biological Autonomous Drilling

Fuente: arXiv
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Autori principali: Lin, Xiaofeng, Zhao, Enduo, Pérez, Saúl Alexis Heredia, Harada, Kanako
Natura: Preprint
Pubblicazione: 2025
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author Lin, Xiaofeng
Zhao, Enduo
Pérez, Saúl Alexis Heredia
Harada, Kanako
author_facet Lin, Xiaofeng
Zhao, Enduo
Pérez, Saúl Alexis Heredia
Harada, Kanako
contents Estimating the state of biological specimens is challenging due to limited observation through microscopic vision. For instance, during mouse skull drilling, the appearance alters little when thinning bone tissue because of its semi-transparent property and the high-magnification microscopic vision. To obtain the object's state, we introduce an object state estimation method for biological specimens through active interaction based on the deflection. The method is integrated to enhance the autonomous drilling system developed in our previous work. The method and integrated system were evaluated through 12 autonomous eggshell drilling experiment trials. The results show that the system achieved a 91.7% successful ratio and 75% detachable ratio, showcasing its potential applicability in more complex surgical procedures such as mouse skull craniotomy. This research paves the way for further development of autonomous robotic systems capable of estimating the object's state through active interaction.
format Preprint
id arxiv_https___arxiv_org_abs_2503_04043
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Object State Estimation Through Robotic Active Interaction for Biological Autonomous Drilling
Lin, Xiaofeng
Zhao, Enduo
Pérez, Saúl Alexis Heredia
Harada, Kanako
Robotics
Systems and Control
Estimating the state of biological specimens is challenging due to limited observation through microscopic vision. For instance, during mouse skull drilling, the appearance alters little when thinning bone tissue because of its semi-transparent property and the high-magnification microscopic vision. To obtain the object's state, we introduce an object state estimation method for biological specimens through active interaction based on the deflection. The method is integrated to enhance the autonomous drilling system developed in our previous work. The method and integrated system were evaluated through 12 autonomous eggshell drilling experiment trials. The results show that the system achieved a 91.7% successful ratio and 75% detachable ratio, showcasing its potential applicability in more complex surgical procedures such as mouse skull craniotomy. This research paves the way for further development of autonomous robotic systems capable of estimating the object's state through active interaction.
title Object State Estimation Through Robotic Active Interaction for Biological Autonomous Drilling
topic Robotics
Systems and Control
url https://arxiv.org/abs/2503.04043