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Biomimetics
Special Issues
Recent Advances in Bioinspired Robot and Intelligent Systems
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Recent Advances in Bioinspired Robot and Intelligent Systems

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: 10 February 2026 | Viewed by 4498

Special Issue Editors

Dr. Guoniu Zhu

E-Mail Website
Guest Editor
Academy for Engineering and Technology, Fudan University, Shanghai 200433, China
Interests: task and motion planning; grasping and dexterous manipulation; biologically inspired design
Special Issues, Collections and Topics in MDPI journals
Dr. Yi Fang

E-Mail Website
Guest Editor
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: industrial robots; motion planning and control; multi-objective intelligent optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Yang Yang

E-Mail Website
Guest Editor
Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China
Interests: creative soft robot designs; bioinspired soft robots; pneumatic soft robots; magnetic soft robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue, entitled "Recent Advances in Bioinspired Robot and Intelligent Systems" in the journal Biomimetics. Bioinspired robotics has emerged as a fascinating and rapidly growing field that draws inspiration from nature to develop innovative and efficient robotic systems. By studying and mimicking the remarkable abilities of biological systems, researchers aim to create robots with enhanced performance, adaptability, and resilience. This research area holds immense potential for advancing robotic technologies and developing solutions to complex challenges in various domains, such as healthcare, environmental monitoring, search and rescue, and space exploration.

This Special Issue aims to showcase the latest advances and trends in the bioinspired design  approaches for robots. We seek to compile a collection of high-quality research articles that explore novel design principles, materials, control systems, and optimization techniques inspired by biological systems. The scope of this Special Issue aligns well with the journal's focus on cutting-edge research in robotics, biomimetics, and intelligent systems. By bringing together a diverse range of contributions from experts in the field, we aim to provide a comprehensive overview of the current state of the art and future directions in bioinspired robot design.

Original research articles and reviews are welcome for this Special Issue. Research areas may include, but are not limited to, the following:

  • Bioinspired design principles and methodologies for robots;
  • Optimal design of bioinspired sensors, actuators, and control systems;
  • Bioinspired materials and structures for soft robotics;
  • Evolutionary algorithms and swarm intelligence for robot optimization;
  • Bioinspired locomotion and manipulation strategies;
  • Biohybrid systems and bioinspired human–robot interaction;
  • Bioinspired energy harvesting and self-healing mechanisms;
  • Applications of bioinspired robots in healthcare, environmental monitoring, and exploration;
  • Bioinspired artificial intelligence and machine learning for robot control and perception;
  • Bioinspired optimization techniques for robot design and performance enhancement.

We look forward to receiving your contributions to this Special Issue and working together to advance the field of bioinspired robotics.

Dr. Guoniu Zhu
Dr. Yi Fang
Dr. Yang Yang
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

  • bioinspired robotics
  • biomimetic design
  • biologically inspired materials
  • bioinspired control systems
  • bioinspired algorithms
  • soft robotics
  • artificial muscles
  • compliant mechanisms
  • intelligent algorithms
  • intelligent systems
  • swarm intelligence

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

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33 pages, 5024 KiB  
Article
An Enhanced Dynamic Model of a Spatial Parallel Mechanism Receiving Direct Constraints from the Base at Two Point-Contact Higher Kinematic Pairs
by Chen Cheng, Xiaojing Yuan and Yenan Li
Biomimetics 2025, 10(7), 437; https://doi.org/10.3390/biomimetics10070437 - 3 Jul 2025
Viewed by 316
Abstract
In this paper, a biologically congruent parallel mechanism (PM) inspired by the masticatory system of human beings has been proposed to recreate complete chewing behaviours in three-dimensional space. The mechanism is featured by direct constraints from the base (DCFB) to its end effector [...] Read more.
In this paper, a biologically congruent parallel mechanism (PM) inspired by the masticatory system of human beings has been proposed to recreate complete chewing behaviours in three-dimensional space. The mechanism is featured by direct constraints from the base (DCFB) to its end effector at two higher kinematic pairs (HKPs), which greatly raise its topological complexity. Meanwhile, friction effects occur at HKPs and actuators, causing wear and then reducing motion accuracy. Regarding these, an inverse dynamic model that can raise the computational efficiency and the modelling fidelity is proposed, being prepared to be applied to realise accurate real-time motion and/or force control. In it, Euler parameters are employed to express the motions of the constrained end effector, and Newton–Euler’s law is applied, which can conveniently incorporate friction effects at both HKPs and actuators into the dynamic model. Numerical results show that the time consumption of the model using Euler parameters is only approximately 23% of that of the model using Euler angles, and friction effects significantly increase the model’s nonlinearity. Further, from the comparison between the models of the target PM and its counterpart free of DCFB, these constraints sharply raise the modelling complexity in terms of the transformation between Euler parameters and Euler angles in the end effector and the computational cost of inverse dynamics. Full article
(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)
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20 pages, 7865 KiB  
Article
Design and Performance of a Neurosurgery Assisting Device
by Karla Nayeli Silva-Garcés, Marco Ceccarelli, Matteo Russo and Christopher René Torres-SanMiguel
Biomimetics 2025, 10(6), 345; https://doi.org/10.3390/biomimetics10060345 - 23 May 2025
Viewed by 2414
Abstract
This paper presents a new design solution for a neurosurgery-assisting device (NeurADe) based on a 3-RPS parallel kinematic mechanism. The NeurADe design employs compact linear actuators to accurately insert a cannula into specific areas of the brain. The CAD design and assembly of [...] Read more.
This paper presents a new design solution for a neurosurgery-assisting device (NeurADe) based on a 3-RPS parallel kinematic mechanism. The NeurADe design employs compact linear actuators to accurately insert a cannula into specific areas of the brain. The CAD design and assembly of a prototype are discussed in this paper. The preliminary NeurADe prototype features 3D printed parts and incorporates mechanical and electrical components, which are designed for ease of use and lightweight functionality. For design validation and operational characterization, sensors measuring current, acceleration, and force data were utilized, and testing results are discussed to prove the feasibility of the proposed design. Full article
(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)
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31 pages, 15164 KiB  
Article
Coordinated Locomotion Control for a Quadruped Robot with Bionic Parallel Torso
by Yaguang Zhu, Ao Cao, Zhimin He, Mengnan Zhou and Ruyue Li
Biomimetics 2025, 10(5), 335; https://doi.org/10.3390/biomimetics10050335 - 20 May 2025
Viewed by 544
Abstract
This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-DOF) bionic active torso based on a parallel mechanism. Inspired by the compliant and flexible torsos of quadrupedal mammals, the proposed torso structure enhances locomotion performance [...] Read more.
This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-DOF) bionic active torso based on a parallel mechanism. Inspired by the compliant and flexible torsos of quadrupedal mammals, the proposed torso structure enhances locomotion performance by enabling coordinated motion between the torso and legs. A complete kinematic model of the bionic torso and the whole body of the quadruped robot is developed. To address the variation in inertial properties caused by torso motion, a model predictive control (MPC) strategy with a variable center of mass (CoM) is proposed for integrated whole-body motion control. Comparative simulations under trot gait are conducted between rigid-torso and active-torso configurations. Results show that the active torso significantly improves gait flexibility, postural stability, and locomotion efficiency. This study provides a new approach to enhancing biomimetic locomotion in quadruped robots through active torso-leg coordination. Full article
(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)
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Review

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39 pages, 5277 KiB  
Review
AI-Driven Control Strategies for Biomimetic Robotics: Trends, Challenges, and Future Directions
by Hoejin Jung, Soyoon Park, Sunghoon Joe, Sangyoon Woo, Wonchil Choi and Wongyu Bae
Biomimetics 2025, 10(7), 460; https://doi.org/10.3390/biomimetics10070460 - 14 Jul 2025
Viewed by 390
Abstract
Biomimetic robotics aims to replicate biological movement, perception, and cognition, drawing inspiration from nature to develop robots with enhanced adaptability, flexibility, and intelligence. The integration of artificial intelligence has significantly advanced the control mechanisms of biomimetic robots, enabling real-time learning, optimization, and adaptive [...] Read more.
Biomimetic robotics aims to replicate biological movement, perception, and cognition, drawing inspiration from nature to develop robots with enhanced adaptability, flexibility, and intelligence. The integration of artificial intelligence has significantly advanced the control mechanisms of biomimetic robots, enabling real-time learning, optimization, and adaptive decision-making. This review systematically examines AI-driven control strategies for biomimetic robots, categorizing recent advancements and methodologies. First, we review key aspects of biomimetic robotics, including locomotion, sensory perception, and cognitive learning inspired by biological systems. Next, we explore various AI techniques—such as machine learning, deep learning, and reinforcement learning—that enhance biomimetic robot control. Furthermore, we analyze existing AI-based control methods applied to different types of biomimetic robots, highlighting their effectiveness, algorithmic approaches, and performance compared to traditional control techniques. By synthesizing the latest research, this review provides a comprehensive overview of AI-driven biomimetic robot control and identifies key challenges and future research directions. Our findings offer valuable insights into the evolving role of AI in enhancing biomimetic robotics, paving the way for more intelligent, adaptive, and efficient robotic systems. Full article
(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)
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