Automate surgical tasks for a flexible Serpentine Manipulator via learning actuation space trajectory from demonstration

Surgical robotic systems with miniaturized flexible Tendon-driven Serpentine Manipulators (TSM) have enjoyed increasing popularities among surgeons and researchers for their advantages of working in constrained and torturous human lumen such as oral cavity and upper GI tract. However, they suffer from sufficient nonlinearities and model uncertainties due to friction, tension varying, tendon slacking, etc. Model based control is insufficient to overcome such uncertainties and automate challenging surgical related tasks. The objective of this work is to automate certain clinical tasks to alleviate surgeon fatigue and promote task efficiency in kinematics free and sensor free circumstances. We present a data-driven approach based on Learning from Demonstration (LfD), which utilizes statistical machine learning models to encode system underlying dynamics and generalize smooth motor trajectories by direct actuation space learning. Motion segmentation is enabled with soft margin Support Vector Machine (soft-SVM) in complicated tasks. We also make attempts to retrieve task-specific properties by Locally Weighted Regression (LWR). We evaluated the approach on two surgical related tasks: compliant insertion and simplified Endoscopic Submucosal Dissection (ESD). The flexible TSM successfully reproduced both tasks and demonstrated superior trajectory performance. A video is available at: https://youtu.be/rLQo6xKtyMI

Recent developments in fibre optic shape sensing

This paper presents a comprehensive critical review of technologies used in the development of fibre optic shape sensors (FOSSs). Their operation is based on multi-dimensional bend measurements using a series of fibre optic sensors. Optical fibre sensors have experienced tremendous growth from simple bend sensors in 1980s to full three-dimensional FOSSs using multicore fibres in recent years. Following a short review of conventional contact-based shape sensor technologies, the evolution trend and sensing principles of FOSSs are presented. This paper identifies the major optical fibre technologies used for shape sensing and provides an account of the challenges and emerging applications of FOSSs in various industries such as medical robotics, industrial robotics, aerospace and mining industry