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Biomimetics
Special Issues
Biomimetic Robot Motion Control
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Biomimetic Robot Motion Control

A special issue of Biomimetics (ISSN 2313-7673).

Deadline for manuscript submissions: 30 January 2026 | Viewed by 674

Special Issue Editors

Dr. Tao Zhang

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Beihang University, Beijing, China
Interests: bioinspired robot; space robot
Prof. Dr. Kun Xu

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Beihang University, Beijing, China
Interests: bioinspired robot; space robot; legged robot; robot control
Dr. Ehsan Asadi

E-Mail Website
Guest Editor
School of Engineering, RMIT University, Melbourne, Australia
Interests: bioinspired robot; field robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Shuaizhong Zhang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
Interests: bioinspired robot; micro-nano robot
Special Issues, Collections and Topics in MDPI journals
Dr. Haifei Zhu

E-Mail Website
Guest Editor
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510520, China
Interests: bioinspired robot; climbing robot
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomimetic robots—robots designed to imitate the motion capabilities of animals, insects, and even plants—are gaining increasing attention due to their ability to navigate in unstructured, dynamic environments where traditional robots often struggle. Using bio-inspired algorithms, actuation systems, and control strategies, these robots can adapt to various terrains, demonstrate agility, and perform complex tasks such as manipulation, exploration, and monitoring.

The field of biomimetic robot motion control holds immense promise for advancing robotics technologies across a range of industries. By learning from the natural world, researchers are developing robots that are not only more capable and efficient but also more adaptable and intelligent. The field of biomimetic robot motion control has seen tremendous growth in recent years as we continue to strive for more adaptive, efficient, and autonomous robots that can interact with complex environments. The emulation of biological systems to inspire robot movement presents exciting possibilities for achieving highly sophisticated, efficient, and versatile motion capabilities. We are pleased to invite you to contribute to this Special Issue, entitled "Biomimetic Robot Motion Control", in the journal of Biomimetics. This Special Issue invites contributions that explore cutting-edge advancements in biomimetic robot motion control, emphasizing the seamless integration of biological principles into robotic systems. We seek original research, review articles, and case studies that explore innovative concepts, methodologies, and technologies in the design, control, and application of biomimetic robots.

We invite papers that address, but are not limited to, the following areas:

  1. Biomimetic motion control strategies;
  2. Biomimetic actuation mechanisms;
  3. Bio-inspired sensor integration and perception;
  4. Machine learning and AI for biomimetic robotics;
  5. Energy efficiency and sustainability in biomimetic robot control;
  6. Biomimetic robot control in complex and extreme environments;
  7. Biohybrid robots and bio-inspired materials;
  8. Multi-modal and hybrid locomotion systems;
  9. Experimental and simulation methods for biomimetic robots;
  10. Biomimetic robotics for real-world applications.

We encourage the submission of real-world applications of biomimetic robots in fields such as environmental monitoring, industrial inspection, medical robotics, search and rescue, and space exploration. Case studies that demonstrate the effectiveness and advantages of bioinspired robots in practical applications will provide valuable insights into their potential and future impact.

We look forward to your contributions to this Special Issue, and to the continued growth and success of biomimetic robot motion control research.

Dr. Tao Zhang
Prof. Dr. Kun Xu
Dr. Ehsan Asadi
Dr. Shuaizhong Zhang
Dr. Haifei Zhu
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. Biomimetics 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 2200 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 motion control
  • AI and machine learning in bio-inspired robotics
  • bio-inspired control algrithms and strategies
  • bio-inspired sensing and feedback control
  • bio-inspired actuation

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Published Papers (3 papers)

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Research

21 pages, 9720 KiB  
Article
Rolling vs. Swing: A Strategy for Enhancing Locomotion Speed and Stability in Legged Robots
by Yongjiang Xue, Wei Wang, Mingyu Duan, Nanqing Jiang, Shaoshi Zhang and Xuan Xiao
Biomimetics 2025, 10(7), 435; https://doi.org/10.3390/biomimetics10070435 - 2 Jul 2025
Abstract
Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the [...] Read more.
Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the energy efficiency and stability. First, a wheel-legged quadruped robot, R-Taichi, is developed, which is capable of switching to legged, wheeled, and RHex mobile modes. Second, the mechanical structure of the transformable two-degree-of-freedom leg is introduced, and the kinematics is analyzed. Finally, experiments are conducted to generate wheeled, legged, and RHex motion in both swing and rolling gaits, and the energy efficiency is further compared. The experimental results show that the rolling motion can ensure stable ground contact and mitigate cyclic collisions, reducing specific resistance by up to 30% compared with conventional swing gaits, achieving a top speed of 0.7 m/s with enhanced stability (root mean square error (RMSE) reduction of 22% over RHex mode). Furthermore, R-Taichi exhibits robust multi-terrain adaptability, successfully traversing gravel, grass, and obstacles up to 150 mm in height. Full article
(This article belongs to the Special Issue Biomimetic Robot Motion Control)
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16 pages, 2524 KiB  
Article
Design of a Hierarchical Control Architecture for Fully-Driven Multi-Fingered Dexterous Hand
by Yinan Jin, Hujiang Wang, Han Ge and Guanjun Bao
Biomimetics 2025, 10(7), 422; https://doi.org/10.3390/biomimetics10070422 - 30 Jun 2025
Abstract
Multi-fingered dexterous hands provide superior dexterity in complex manipulation tasks due to their high degrees of freedom (DOFs) and biomimetic structures. Inspired by the anatomical structure of human tendons and muscles, numerous robotic hands powered by pneumatic artificial muscles (PAMs) have been created [...] Read more.
Multi-fingered dexterous hands provide superior dexterity in complex manipulation tasks due to their high degrees of freedom (DOFs) and biomimetic structures. Inspired by the anatomical structure of human tendons and muscles, numerous robotic hands powered by pneumatic artificial muscles (PAMs) have been created to replicate the compliant and adaptable features of biological hands. Nonetheless, PAMs have inherent nonlinear and hysteresis behaviors that create considerable challenges to achieving real-time control accuracy and stability in dexterous hands. In order to address these challenges, this paper proposes a hierarchical control architecture that employs a fuzzy PID strategy to optimize the nonlinear control of pneumatic artificial muscles (PAMs). The FPGA-based hardware integrates a multi-channel digital-to-analog converter (DAC) and a multiplexed acquisition module, facilitating the independent actuation of 20 PAMs and the real-time monitoring of 20 joints. The software implements a fuzzy PID algorithm that dynamically adjusts PID parameters based on both the error and the error rate, thereby effectively managing the nonlinear behaviors of the hand. Experimental results demonstrate that the designed control system achieves high precision in controlling the angle of a single finger joint, with errors maintained within ±1°. In scenarios involving multi-finger cooperative grasping and biomimetic motion demonstrations, the system exhibits excellent synchronization and real-time performance. These results validate the efficacy of the fuzzy PID control strategy and confirm that the proposed system fulfills the precision and stability requirements for complex operational tasks, providing robust support for the application of PAM-driven multi-fingered dexterous hands. Full article
(This article belongs to the Special Issue Biomimetic Robot Motion Control)
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28 pages, 6847 KiB  
Article
Bionic Energy-Efficient Inverse Kinematics Method Based on Neural Networks for the Legs of Hydraulic Legged Robots
by Jinbo She, Xiang Feng, Bao Xu, Linyang Chen, Yuan Wang, Ning Liu, Wenpeng Zou, Guoliang Ma, Bin Yu and Kaixian Ba
Biomimetics 2025, 10(6), 403; https://doi.org/10.3390/biomimetics10060403 - 14 Jun 2025
Viewed by 314
Abstract
Hydraulic legged robots, with advantages such as high load capacity and power density, have become a strategic driving force in advancing intelligent mobile platform technologies. However, their high energy consumption significantly limits long-duration endurance and efficient operational performance. In this paper, inspired by [...] Read more.
Hydraulic legged robots, with advantages such as high load capacity and power density, have become a strategic driving force in advancing intelligent mobile platform technologies. However, their high energy consumption significantly limits long-duration endurance and efficient operational performance. In this paper, inspired by the excellent autonomous energy-efficient consciousness of mammals endowed by natural evolution, a bionic energy-efficient inverse kinematics method based on neural networks (EIKNN) is proposed for the energy-efficient motion planning of hydraulic legged robots with redundant degrees of freedom (RDOFs). Firstly, the dynamic programming (DP) algorithm is used to solve the optimal joint configuration with minimum energy loss as the goal, and the training data set is generated. Subsequently, the inverse kinematic model of the leg with minimum energy loss is learned based on neural network (NN) simulation of the autonomous energy-efficient consciousness endowed to mammals by natural evolution. Finally, extensive comparative experiments validate the effectiveness and superiority of the proposed method. This method not only significantly reduces energy dissipation in hydraulic legged robots but also lays a crucial foundation for advancing hydraulic legged robot technology toward high efficiency, environmental sustainability, and long-term developmental viability. Full article
(This article belongs to the Special Issue Biomimetic Robot Motion Control)
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