98 citations · 152 across the 17 of their papers we have counts for
17 papers
Bio-inspired fine-tuning for selective transfer learning in image classification
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Deep learning has significantly advanced image analysis across diverse domains but often depends on large, annotated datasets for success. Transfer learning addresses this challeng…
Development of a Compliant Gripper for Safe Robot-Assisted Trouser Dressing-Undressing
Jayant Unde, Takumi Inden, Yuki Wakayama +4
In recent years, many countries, including Japan, have rapidly aging populations, making the preservation of seniors' quality of life a significant concern. For elderly people with…
Adaptive transfer learning for surgical tool presence detection in laparoscopic videos through gradual freezing fine-tuning
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Minimally invasive surgery can benefit significantly from automated surgical tool detection, enabling advanced analysis and assistance. However, the limited availability of annotat…
Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Effective human-robot collaboration in surgery is affected by the inherent ambiguity of verbal communication. This paper presents a framework for a robotic surgical assistant that…
Transfer learning optimization based on evolutionary selective fine tuning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Deep learning has shown substantial progress in image analysis. However, the computational demands of large, fully trained models remain a consideration. Transfer learning offers a…
Assessing the Value of Visual Input: A Benchmark of Multimodal Large Language Models for Robotic Path Planning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Large Language Models (LLMs) show potential for enhancing robotic path planning. This paper assesses visual input's utility for multimodal LLMs in such tasks via a comprehensive be…
Beyond Single Models: Enhancing LLM Detection of Ambiguity in Requests through Debate
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Large Language Models (LLMs) have demonstrated significant capabilities in understanding and generating human language, contributing to more natural interactions with complex syste…
LLM-based ambiguity detection in natural language instructions for collaborative surgical robots
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Ambiguity in natural language instructions poses significant risks in safety-critical human-robot interaction, particularly in domains such as surgery. To address this, we propose…
Human-Robot collaboration in surgery: Advances and challenges towards autonomous surgical assistants
Jacinto Colan, Ana Davila, Yutaro Yamada +1
Human-robot collaboration in surgery represents a significant area of research, driven by the increasing capability of autonomous robotic systems to assist surgeons in complex proc…
Voice control interface for surgical robot assistants
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Traditional control interfaces for robotic-assisted minimally invasive surgery impose a significant cognitive load on surgeons. To improve surgical efficiency, surgeon-robot collab…
Embedded Image-to-Image Translation for Efficient Sim-to-Real Transfer in Learning-based Robot-Assisted Soft Manipulation
Jacinto Colan, Keisuke Sugita, Ana Davila +2
Recent advances in robotic learning in simulation have shown impressive results in accelerating learning complex manipulation skills. However, the sim-to-real gap, caused by discre…
A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery
Jacinto Colan, Ana Davila, Khusniddin Fozilov +1
Minimally invasive surgery (MIS) procedures benefit significantly from robotic systems due to their improved precision and dexterity. However, ensuring safety in these dynamic and…
Comparison of fine-tuning strategies for transfer learning in medical image classification
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
In the context of medical imaging and machine learning, one of the most pressing challenges is the effective adaptation of pre-trained models to specialized medical contexts. Despi…
Manipulability maximization in constrained inverse kinematics of surgical robots
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
In robot-assisted minimally invasive surgery (RMIS), inverse kinematics (IK) must satisfy a remote center of motion (RCM) constraint to prevent tissue damage at the incision point.…
Task segmentation based on transition state clustering for surgical robot assistance
Yutaro Yamada, Jacinto Colan, Ana Davila +1
Understanding surgical tasks represents an important challenge for autonomy in surgical robotic systems. To achieve this, we propose an online task segmentation framework that uses…
Constrained Motion Planning for a Robotic Endoscope Holder based on Hierarchical Quadratic Programming
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Minimally Invasive Surgeries (MIS) are challenging for surgeons due to the limited field of view and constrained range of motion imposed by narrow access ports. These challenges ca…
Cutaneous Feedback Interface for Teleoperated In-Hand Manipulation
Yaonan Zhu, Jacinto Colan, Tadayoshi Aoyama +1
In-hand pivoting is one of the important manipulation skills that leverage robot grippers' extrinsic dexterity to perform repositioning tasks to compensate for environmental uncert…