← Search

Alicia Casals

7 accepted papers

2023

Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation

IROS 2023poster

The field of robotic Flexible Endoscopes (FEs) has progressed significantly, offering a promising solution to reduce patient discomfort. However, the limited autonomy of most robotic FEs results in non-intuitive and challenging manoeuvres, constraining their application in clinical settings. While p…

Cited by 9SourceScholar
2022

Colonoscopy Navigation using End-to-End Deep Visuomotor Control: A User Study

IROS 2022poster

Flexible Endoscopes (FEs) for colonoscopy present several limitations due to their inherent complexity, resulting in patient discomfort and lack of intuitiveness for clinicians. Robotic FEs with autonomous control represent a viable solution to reduce the workload of endoscopists and the training ti…

Cited by 16SourcecodeScholar
2021

Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery

IROS 2021poster

Deep Reinforcement Learning (DRL) is a viable solution for automating repetitive surgical subtasks due to its ability to learn complex behaviours in a dynamic environment. This task automation could lead to reduced surgeon’s cognitive workload, increased precision in critical aspects of the surgery,…

Cited by 59SourcecodeScholar
2020

Global/local motion planning based on Dynamic Trajectory Reconfiguration and Dynamical Systems for Autonomous Surgical Robots

ICRA 2020poster

This paper addresses the generation of collision-free trajectories for the autonomous execution of assistive tasks in Robotic Minimally Invasive Surgery (R-MIS). The proposed approach takes into account geometric constraints related to the desired task, like for example the direction to approach the…

Cited by 8SourceScholar
2018

Estimation of Interaction Forces in Robotic Surgery using a Semi-Supervised Deep Neural Network Model

IROS 2018poster

Providing force feedback as a feature in current Robot-Assisted Minimally Invasive Surgery systems still remains a challenge. In recent years, Vision-Based Force Sensing (VBFS) has emerged as a promising approach to address this problem. Existing methods have been developed in a Supervised Learning…

Cited by 28SourceScholar
2017

Sight to touch: 3D diffeomorphic deformation recovery with mixture components for perceiving forces in robotic-assisted surgery

IROS 2017poster

Robotic-assisted minimally invasive surgical systems suffer from one major limitation which is the lack of interaction forces feedback. The restricted sense of touch hinders the surgeons' performance and reduces their dexterity and precision during a procedure. In this work, we present a sensory sub…

Cited by 9SourceScholar