Single-Shot Pose Estimation of Surgical Robot Instruments' Shafts from Monocular Endoscopic Images

Masakazu Yoshimura, Murilo M. Marinho, Kanako Harada, Mamoru Mitsuishi

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

Abstract

Surgical robots are used to perform minimally invasive surgery and alleviate much of the burden imposed on surgeons. Our group has developed a surgical robot to aid in the removal of tumors at the base of the skull via access through the nostrils. To avoid injuring the patients, a collision-avoidance algorithm that depends on having an accurate model for the poses of the instruments' shafts is used. Given that the model's parameters can change over time owing to interactions between instruments and other disturbances, the online estimation of the poses of the instrument's shaft is essential. In this work, we propose a new method to estimate the pose of the surgical instruments' shafts using a monocular endoscope. Our method is based on the use of an automatically annotated training dataset and an improved pose-estimation deep-learning architecture. In preliminary experiments, we show that our method can surpass state of the art vision-based marker-less pose estimation techniques (providing an error decrease of 55% in position estimation, 64% in pitch, and 69% in yaw) by using artificial images.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation, ICRA 2020
PublisherIEEE
Pages9960-9966
Number of pages7
ISBN (Electronic)9781728173955
DOIs
Publication statusPublished - May 2020
Event2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
Duration: 31 May 202031 Aug 2020

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Country/TerritoryFrance
CityParis
Period31/05/2031/08/20

Fingerprint

Dive into the research topics of 'Single-Shot Pose Estimation of Surgical Robot Instruments' Shafts from Monocular Endoscopic Images'. Together they form a unique fingerprint.

Cite this