RCM-SLAM: Visual localisation and mapping under remote centre of motion constraints
Francisco Vasconcelos, Evangelos Mazomenos, John Kelly, Danail Stoyanov
Abstract
In robotic surgery the motion of instruments and the laparoscopic camera is constrained by their insertion ports, i. e. a remote centre of motion (RCM). We propose a Simultaneous Localisation and Mapping (SLAM) approach that estimates laparoscopic camera motion under RCM constraints. To achieve this we derive a minimal solver for the absolute camera pose given two 2D-3D point correspondences (RCM-PnP) and also a bundle adjustment optimiser that refines camera poses within an RCM-constrained parameterisation. These two methods are used together with previous work on relative pose estimation under RCM [1] to assemble a SLAM pipeline suitable for robotic surgery. Our simulations show that RCM-PnP outperforms conventional PnP for a wide noise range in the RCM position. Results with video footage from a robotic prostatectomy show that RCM constraints significantly improve camera pose estimation.
BibTeX
@inproceedings{icra2019_rcmslamvisualloc,
title = {RCM-SLAM: Visual localisation and mapping under remote centre of motion constraints},
author = {Francisco Vasconcelos and Evangelos Mazomenos and John Kelly and Danail Stoyanov},
booktitle = {ICRA 2019},
year = {2019}
}