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Micromachines
Special Issues
Soft Robotics: Challenges and Perspectives
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Soft Robotics: Challenges and Perspectives

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A：Physics".

Deadline for manuscript submissions: closed (15 July 2022) | Viewed by 2965

Special Issue Editor

Prof. Tiefeng Li

E-Mail Website
Guest Editor
Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province, X-Mechanics Center, Department of Engineering Mechanics, Zhejiang University, Hangzhou 310027, China
Interests: solid mechanics; soft matter; soft robotics; smart material and structures

Special Issue Information

Dear Colleagues,

Soft robots driven by soft active materials have unique advantages over conventional rigid robots, especially in their high adaptability for field exploration, morphing design and seamless interaction with humans. The grand challenge lies in achieving self-powered soft robots with high mobility, robust control, environmental tolerance, and long endurance. The design principle, modeling and control strategies can be potentially extended to a variety of flexible devices and soft robots.

Prof. Tiefeng Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Underwater soft robot
  • Morphing structure control
  • Bio-inspired smart structure
  • Soft smart material

Published Papers (1 paper)

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Research

13 pages, 1605 KiB  
Article
A Novel Distribution for Representation of 6D Pose Uncertainty
by Lei Zhang, Huiliang Shang and Yandan Lin
Micromachines 2022, 13(1), 126; https://doi.org/10.3390/mi13010126 - 13 Jan 2022
Cited by 10 | Viewed by 2247
Abstract
The 6D Pose estimation is a crux in many applications, such as visual perception, autonomous navigation, and spacecraft motion. For robotic grasping, the cluttered and self-occlusion scenarios bring new challenges to the this field. Currently, society uses CNNs to solve this problem. The [...] Read more.
The 6D Pose estimation is a crux in many applications, such as visual perception, autonomous navigation, and spacecraft motion. For robotic grasping, the cluttered and self-occlusion scenarios bring new challenges to the this field. Currently, society uses CNNs to solve this problem. The CNN models will suffer high uncertainty caused by the environmental factors and the object itself. These models usually maintain a Gaussian distribution, which is not suitable for the underlying manifold structure of the pose. Many works decouple rotation from the translation and quantify rotational uncertainty. Only a few works pay attention to the uncertainty of the 6D pose. This work proposes a distribution that can capture the uncertainty of the 6D pose parameterized by the dual quaternions, meanwhile, the proposed distribution takes the periodic nature of the underlying structure into account. The presented results include the normalization constant computation and parameter estimation techniques of the distribution. This work shows the benefits of the proposed distribution, which provides a more realistic explanation for the uncertainty in the 6D pose and eliminates the drawback inherited from the planar rigid motion. Full article
(This article belongs to the Special Issue Soft Robotics: Challenges and Perspectives)
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