Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Yang-Xue-An-Tai Decoction Treats URSA by regulating the differentiation of proliferating decidual stromal cells through multiple targets.

Journal of ethnopharmacology·2026
Same author

Effect of age, sex, and BMI on serum olanzapine levels and their correlation with metabolic parameters and serum pro-inflammatory cytokine levels in schizophrenia patients.

BMC psychiatry·2026
Same author

Carbon monoxide-releasing molecule-3 eradicates mature <i>Enterococcus faecalis</i> biofilms and inhibits recolonization.

Journal of biomaterials applications·2026
Same author

Enhancing Cross-scale Feature Mutual Information via Heterogeneous Graph Contrastive Learning for Drug-Target Binding Affinity Prediction.

IEEE journal of biomedical and health informatics·2026
Same author

CDCSI: a machine learning-based interpretable cell death and cellular senescence index for prognosis improvement, immune landscape characterization, and therapeutic response prediction in head and neck squamous cell carcinoma.

Frontiers in immunology·2026
Same author

Itraconazole for infantile hemangiomas: Real-world experience in 90 infants.

Journal of the American Academy of Dermatology·2026

Related Experiment Video

Updated: May 13, 2025

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery
11:06

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery

Published on: November 14, 2015

8.9K

Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints.

Xian He1,2, Shuai Zhang1,2, Jian Chu1,2

  • 1School of Management, Hefei University of Technology, Hefei, China.

Cyborg and Bionic Systems (Washington, D.C.)
|April 15, 2025
PubMed
Summary

This study introduces an intuition-guided deep reinforcement learning framework for autonomous robotic surgery. The ID-SAC system enhances soft tissue manipulation by navigating unknown constraints and obstacles, improving surgical precision.

More Related Videos

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
07:49

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation

Published on: August 2, 2016

8.7K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

8.7K

Related Experiment Videos

Last Updated: May 13, 2025

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery
11:06

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery

Published on: November 14, 2015

8.9K
Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
07:49

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation

Published on: August 2, 2016

8.7K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

8.7K

Area of Science:

  • Robotics
  • Surgical Technology
  • Artificial Intelligence

Background:

  • Autonomous robotic surgery faces challenges in soft tissue manipulation due to complex in vivo environments.
  • Prior research often simplified constraints, assuming known grasping points and constant operational conditions, neglecting obstacles.

Purpose of the Study:

  • To develop an advanced framework for autonomous soft tissue manipulation under unknown and dynamic constraints.
  • To enhance robotic decision-making in intricate surgical scenarios.

Main Methods:

  • Proposed an intuition-guided deep reinforcement learning framework (ID-SAC) integrating soft actor-critic (SAC) with an intuitive manipulation (IM) strategy.
  • Implemented an autonomous grasp point selection neural network to ensure practical and safe grasping.
  • Introduced a regulator factor for coordinating manipulation strategies and a reward function for optimizing exploration.

Main Results:

  • The ID-SAC framework successfully manipulated soft tissues while avoiding obstacles and adapting to new positional constraints in simulations.
  • The system demonstrated improved robotic soft tissue manipulation compared to the standard SAC algorithm.
  • Automatic adjustment of regulator factors by the framework enhanced performance.

Conclusions:

  • The proposed ID-SAC framework offers a robust solution for autonomous soft tissue manipulation in challenging surgical environments.
  • This approach significantly advances the capabilities of robotic surgery by addressing limitations in handling unknown constraints and obstacles.