Dataset Information

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator.

ABSTRACT: A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as the Robostrich arm. This study particularly focused on the control problems and simulation development of such a tendon-driven high-DOF underactuated manipulator. We proposed a curriculum-based reinforcement-learning approach. Inspired by human learning, progressing from simple to complex tasks, the Robostrich arm can obtain manipulation abilities by step-by-step reinforcement learning ranging from simple position control tasks to practical application tasks. In addition, an approach was developed to simulate tendon-driven manipulation with a complicated structure. The results show that the Robostrich arm can continuously reach various targets and simultaneously maintain its tip at the desired orientation while mounted on a mobile platform in the presence of perturbation. These results show that our system can achieve flexible manipulation ability even if vibrations are presented by locomotion.

SUBMITTER: Or K

PROVIDER: S-EPMC10369056 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator.

Or Keung K Wu Kehua K Nakano Kazashi K Ikeda Masahiro M Ando Mitsuhito M Kuniyoshi Yasuo Y Niiyama Ryuma R

Frontiers in robotics and AI 20230712

A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as ...[more]

PMID: 37501743

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Project description:PurposeThe use of robotic continuum manipulators has been proposed to facilitate less-invasive orthopedic surgical procedures. While tools and strategies have been developed, critical challenges such as system control and intra-operative guidance are under-addressed. Simulation tools can help solve these challenges, but several gaps limit their utility for orthopedic surgical systems, particularly those with continuum manipulators. Herein, a simulation platform which addresses these gaps is presented as a tool to better understand and solve challenges for minimally invasive orthopedic procedures.MethodsAn open-source surgical simulation software package was developed in which a continuum manipulator can interact with any volume model such as to drill bone volumes segmented from a 3D computed tomography (CT) image. Paired simulated X-ray images of the scene can also be generated. As compared to previous works, tool-anatomy interactions use a physics-based approach which leads to more stable behavior and wider procedure applicability. A new method for representing low-level volumetric drilling behavior is also introduced to capture material variability within bone as well as patient-specific properties from a CT.ResultsSimilar interaction between a continuum manipulator and phantom bone was also demonstrated between a simulated manipulator and volumetric obstacle models. High-level material- and tool-driven behavior was shown to emerge directly from the improved low-level interactions, rather than by need of manual programming.ConclusionThis platform is a promising tool for developing and investigating control algorithms for tasks such as curved drilling. The generation of simulated X-ray images that correspond to the scene is useful for developing and validating image guidance models. The improvements to volumetric drilling offer users the ability to better tune behavior for specific tools and procedures and enable research to improve surgical simulation model fidelity. This platform will be used to develop and test control algorithms for image-guided curved drilling procedures in the femur.

Dataset Information

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator.

Publications

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator.

Similar Datasets

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