Special Issue "Advances in Bio-Inspired Robots"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editors

Prof. Dr. TaeWon Seo
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Guest Editor
School of Mechanical Engineering, Hanyang University, Seoul 04763, Korea
Interests: robot mechanism design; service robot; bio-inspired robot; robot control; optimal design
Prof. Dr. Dongwon Yun
Website
Guest Editor
Department of Robotics Engineering, Daegu Gyeongbuk Institute of Science & Technology (DIGST), Daegu 42988, Korea
Interests: bio-mimetic robot; robot design and control; industrial robot; military robot; mechatronics system
Prof. Dr. Gwang-Pil Jung
Website
Guest Editor
Department of Mechanical & Automotive Engineering, SeoulTech, Seoul 01811, Korea
Interests: milli-scale robotic systems; origami-inspired robots; bio-mimetic robots; soft robots

Special Issue Information

Dear Colleagues,

Bio-inspiration can be a good starting point to design a robotic system, controllers, sensors, and a learning algorithm. Observations of animals and plants can lead to new ideas that humans have not thought of. Making good use of these ideas can help researchers to create more creative and efficient robots. For this reason, research on developing robots by mimicking the shape and motion of animals and plants has been conducted. If these bio-inspiration techniques are used well, they can provide clues to overcome the limitations of conventional robots. Bio-inspiration is also in the spotlight for its potential use in robots for military and environmental monitoring because bio-inspired robots have excellent cover characteristics by copying the shape and movement of animals in nature. The efficient movement of animals is also a key design reference for the development of highly efficient robots. This Special Issue is designed to provide an opportunity to introduce and share state-of-the-art research in the field of bio-inspired robots by collecting and introducing recent research results of various bio-inspired robots. We look forward to the participation of researchers who are conducting research in this field.

Prof. Dr. TaeWon Seo
Prof. Dr. Dongwon Yun
Prof. Dr. Gwang-Pil Jung
Guest Editors

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 papers will be 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 1800 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

  • bio-inspired robotics
  • bio-inspired design
  • bio-mimetic
  • bio-inspired motor control
  • bio-inspired leaning
  • bio-inspired sensing system
  • origami robots
  • soft robotics
  • bio-inspired robotic applications

Published Papers (2 papers)

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Research

Open AccessArticle
Snake Robot with Driving Assistant Mechanism
Appl. Sci. 2020, 10(21), 7478; https://doi.org/10.3390/app10217478 - 24 Oct 2020
Abstract
Snake robots are composed of multiple links and joints and have a high degree of freedom. They can perform various motions and can overcome various terrains. Snake robots need additional driving algorithms and sensors that acquire terrain data in order to overcome rough [...] Read more.
Snake robots are composed of multiple links and joints and have a high degree of freedom. They can perform various motions and can overcome various terrains. Snake robots need additional driving algorithms and sensors that acquire terrain data in order to overcome rough terrains such as grasslands and slopes. In this study, we propose a driving assistant mechanism (DAM), which assists locomotion without additional driving algorithms and sensors. In this paper, we confirmed that the DAM prevents a roll down on a slope and increases the locomotion speed through dynamic simulation and experiments. It was possible to overcome grasslands and a 27 degrees slope without using additional driving controllers. In conclusion, we expect that a snake robot can conduct a wide range of missions well, such as exploring disaster sites and rough terrain, by using the proposed mechanism. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Robots)
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Open AccessArticle
Energy-Efficient Hip Joint Offsets in Humanoid Robot via Taguchi Method and Bio-inspired Analysis
Appl. Sci. 2020, 10(20), 7287; https://doi.org/10.3390/app10207287 - 18 Oct 2020
Abstract
Although previous research has improved the energy efficiency of humanoid robots to increase mobility, no study has considered the offset between hip joints to this end. Here, we optimized the offsets of hip joints in humanoid robots via the Taguchi method to maximize [...] Read more.
Although previous research has improved the energy efficiency of humanoid robots to increase mobility, no study has considered the offset between hip joints to this end. Here, we optimized the offsets of hip joints in humanoid robots via the Taguchi method to maximize energy efficiency. During optimization, the offsets between hip joints were selected as control factors, and the sum of the root-mean-square power consumption from three actuated hip joints was set as the objective function. We analyzed the power consumption of a humanoid robot model implemented in physics simulation software. As the Taguchi method was originally devised for robust optimization, we selected turning, forward, backward, and sideways walking motions as noise factors. Through two optimization stages, we obtained near-optimal results for the humanoid hip joint offsets. We validated the results by comparing the root-mean-square (RMS) power consumption of the original and optimized humanoid models, finding that the RMS power consumption was reduced by more than 25% in the target motions. We explored the reason for the reduction of power consumption through bio-inspired analysis from human gait mechanics. As the distance between the left and right hip joints in the frontal plane became narrower, the amplitude of the sway motion of the upper body was reduced. We found that the reduced sway motion of the upper body of the optimized joint configuration was effective in improving energy efficiency, similar to the influence of the pathway of the body’s center of gravity (COG) on human walking efficiency. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Robots)
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