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Machines
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Design and Application of Bionic Robots
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Design and Application of Bionic Robots

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2229

Special Issue Editors

Prof. Dr. Gang Chen

E-Mail Website
Guest Editor
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Interests: bionic underwater robots; intelligent control in bionic robots; reinforcement learning of robots; dynamics modeling in robotics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Huosheng Hu

E-Mail Website
Guest Editor
School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK
Interests: robotics; embedded systems; mechatronics; advanced manufacturing; multimodal human–machine interfaces; wearable sensors and systems; sensor integration and data fusion algorithms; biomedical signal processing; e-health; medical and surgical robotics; AI applications; intelligent control and learning algorithms; cooperative robots in search and rescue; networked sensors, systems, and robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue titled "Design and Application of Bionic Robots" aims to explore the latest advancements and innovations in the field of bionic robots, focusing on the design principles, technologies, and applications inspired by nature. This issue will cover a wide range of topics, including but not limited to the development of robots that mimic the movement, sensing, and behavior of animals and insects, as well as the integration of advanced materials, sensors, and control algorithms to enhance their performance. The articles in this issue will highlight the potential of bionic robots in various fields, such as search and rescue, environmental monitoring, medical assistance, and agriculture, among others. The goal of this Special Issue is to provide a platform for researchers, engineers, and practitioners to share their insights, experiences, and challenges in designing and applying bionic robots and to promote collaboration and innovation in this exciting and rapidly evolving field.

Prof. Dr. Gang Chen
Prof. Dr. Huosheng Hu
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 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. Machines 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 2400 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

  • bionic robot
  • biomimetic robotics
  • nature-inspired design
  • sensors and control algorithms
  • bionic systems and robots
  • animal and insect movement
  • bionic robot application
  • medical assistance
  • agriculture robots
  • bionic robot for search and rescue
  • bionic legged robots
  • bionic underwater robots

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Published Papers (1 paper)

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Research

23 pages, 10631 KiB  
Article
Multi-Agent Reinforcement Learning Tracking Control of a Bionic Wheel-Legged Quadruped
by Rezwan Al Islam Khan, Chenyun Zhang, Zhongxiao Deng, Anzheng Zhang, Yuzhen Pan, Xuan Zhao, Huiliang Shang and Ruijiao Li
Machines 2024, 12(12), 902; https://doi.org/10.3390/machines12120902 - 9 Dec 2024
Viewed by 1753
Abstract
This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating [...] Read more.
This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating each leg as an independent agent with the goal of autonomous learning. The framework involves a multi-agent setup to model torso and leg dynamics, incorporating motion guidance optimization signal in the policy training and reward function. By doing so, we address leg schedule patterns for the complex configuration of the Pegasus, the requirement for various gaits, and the design of reward functions for MA-RL agents. Agents were trained using two variations of policy networks based on the framework, and real-world tests show promising results with easy policy transfer from simulation to the actual hardware. The proposed framework models acquired higher rewards and converged faster in training than other variants. Various experiments on the robot deployed framework showed fast response (0.8 s) under disturbance and low linear, angular velocity, and heading error, which was 2.5 cm/s, 0.06 rad/s, and 4°, respectively. Overall, the study demonstrates the feasibility of the proposed MA-RL control framework. Full article
(This article belongs to the Special Issue Design and Application of Bionic Robots)
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