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Florent Nageotte

8 accepted papers

2025

Probabilistic Motion Model Learning for Tendon Actuated Continuum Robots with Backlash

IROS 2025

In this paper, we propose a probabilistic motion model for tendon actuated continuum robots that experience actuation transmission non-linearities due to cable slack and cable-sheath friction. The model is based on a Lie group formulation of the robot’s end-effector pose that incorporates a new simp

Cited by 0SourceScholar
2024

Autonomous Guidewire Navigation in Dynamic Environments

IROS 2024poster

Cardiovascular disease treatment involves the challenging task of navigating guidewires and catheters through the vascular anatomy. This often results in prolonged procedures where both the patient and clinician are subjected to X-ray radiation. As a potential solution, Deep Reinforcement Learning m…

Cited by 4SourceScholar
2021

Image-Guided Control of an Endoscopic Robot for OCT Path Scanning

RA-L 2021

Optical coherence tomography (OCT) endoscopic catheters provide efficient solutions for the non-invasive scan of malignant tissues in internal human organs. In this letter, we investigate the image-guided control of a robotic flexible endoscopic system equipped with an OCT probe for autonomous tissu

Cited by 22SourceScholar
2021

Simultaneous haptic guidance and learning of task parameters during robotic teleoperation – a geometrical approach

ICRA 2021poster

Haptic guidance can improve accuracy and dexterity during the teleoperation of a robot, but only if the model of the task used to provide the assistance is accurate. In medical robotics, the registration of a task from pre-operative planning from medical images to the robot’s task-space can be erron…

Cited by 2SourceScholar
2021

Surgical Tool Segmentation Using Generative Adversarial Networks With Unpaired Training Data

RA-L 2021

Surgical tool segmentation is a challenging and crucial task for computer and robot-assisted surgery. Supervised learning approaches have shown great success for this task. However, they need a large number of paired training data. Based on Generative Adversarial Networks (GAN), unpaired image-to-im

Cited by 20SourceScholar
2020

Towards In Situ Backlash Estimation of Continuum Robots Using an Endoscopic Camera

RA-L 2020

Accurate control of continuum robots requires handling non-linear behaviors between actuators and distal effectors. In this letter, we develop a method for estimating the non-linearities of tendon-driven degrees of freedom of flexible endoscopic systems by using a distal endoscopic camera and encode

Cited by 15SourceScholar
2019

Position control of medical cable-driven flexible instruments by combining machine learning and kinematic analysis

ICRA 2019poster

Non-linearities in cable transmissions are important limitations for the accurate control of flexible instruments used in medical endoscopic systems. Hysteresis effects greatly impact the accuracy of conventional kinematic models. This is especially critical for implementing automatic motions in fle…

Cited by 32SourceScholar
2015

A novel marker for estimating the pose of a CT-guided robotic device using a single slice

ICRA 2015poster

Automatic robot / Computed Tomography (CT) scanner registration is an important feature for robot-assisted percutaneous needle placement under CT-scanner. This registration can be done using 3D images, but for fast, low X-ray radiation it is interesting to be able to perform the registration with a…

Cited by 0SourceScholar