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Biomimetics
Special Issues
Computer-Aided Biomimetics: 3rd Edition
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Computer-Aided Biomimetics: 3rd Edition

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Biological Optimisation and Management".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1373

Special Issue Editors

Dr. Honghao Zhang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Shandong University, Jinan 250061, China
Interests: bionic structure design; biomaterials; numerical simulation; multidisciplinary optimization
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yong Peng

E-Mail Website
Guest Editor
School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Interests: bionic structure design; traffic and vehicle crash safety; simulation; optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Danqi Wang

E-Mail Website
Guest Editor
School of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Interests: conceptual design; structural safety and energy saving design; multidisciplinary optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Dongkai Chu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Shandong University, Jinan 250061, China
Interests: bionic structure design; optimization; processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer-aided biomimetics is an interdisciplinary research field that combines computer science and biomimetics. Drawing inspiration from nature's excellent designs, computer-aided biomimetics utilizes computer modeling and simulation techniques to mimic biological systems and apply the derived design and optimization insights to engineering and scientific fields. It finds wide-ranging applications and potential in areas such as materials science, mechanical engineering, aerospace, medicine, energy, and many more. The emergence of computer-aided biomimetics opens up new possibilities for engineers and scientists to tackle real-world problems and holds the potential to drive technological innovation and scientific progress in the future. Many advanced technologies have been applied to the field of computer-aided biomimetics.

The purpose of this Special Issue is to incorporate the latest research studies in the field of advanced methods and applications, from either theoretical or practical perspectives. The relevant topics for this Special Issue include, but are not limited to, the following areas:

  • Multiscale modeling and design of material structures;
  • Conceptual design and biostructure design;
  • Bionic functional surface and bionic structure processing;
  • Mechanical structure and motion control of robots based on bionics principles;
  • Performance analysis and evaluation of computer-aided biomimetics;
  • Multidisciplinary optimization algorithms for computer-aided biomimetics;
  • Application of AI in computer-aided biomimetics;
  • Other related research topics.

Dr. Honghao Zhang
Prof. Dr. Yong Peng
Dr. Danqi Wang
Dr. Dongkai Chu
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

  • computer modeling
  • numerical simulation
  • bionic structures
  • design and optimization
  • motion control
  • bionic functional surface
  • performance analysis

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

Related Special Issue

Published Papers (3 papers)

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Research

14 pages, 831 KB  
Article
Migratory Bird-Inspired Adaptive Kalman Filtering for Robust Navigation of Autonomous Agricultural Planters in Unstructured Terrains
by Zijie Zhou, Yitao Huang and Jiyu Sun
Biomimetics 2025, 10(8), 543; https://doi.org/10.3390/biomimetics10080543 - 19 Aug 2025
Viewed by 231
Abstract
This paper presents a bionic extended Kalman filter (EKF) state estimation algorithm for agricultural planters, inspired by the bionic mechanism of migratory birds navigating in complex environments, where migratory birds achieve precise localization behaviors by fusing multi-sensory information (e.g., geomagnetic field, visual landmarks, [...] Read more.
This paper presents a bionic extended Kalman filter (EKF) state estimation algorithm for agricultural planters, inspired by the bionic mechanism of migratory birds navigating in complex environments, where migratory birds achieve precise localization behaviors by fusing multi-sensory information (e.g., geomagnetic field, visual landmarks, and somatosensory balance). The algorithm mimics the migratory bird’s ability to integrate multimodal information by fusing laser SLAM, inertial measurement unit (IMU), and GPS data to estimate the position, velocity, and attitude of the planter in real time. Adopting a nonlinear processing approach, the EKF effectively handles nonlinear dynamic characteristics in complex terrain, similar to the adaptive response of a biological nervous system to environmental perturbations. The algorithm demonstrates bio-inspired robustness through the derivation of the nonlinear dynamic teaching model and measurement model and is able to provide high-precision state estimation in complex environments such as mountainous or hilly terrain. Simulation results show that the algorithm significantly improves the navigation accuracy of the planter in unstructured environments. A new method of bio-inspired adaptive state estimation is provided. Full article
(This article belongs to the Special Issue Computer-Aided Biomimetics: 3rd Edition)
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33 pages, 10397 KB  
Article
Multi-AUV Dynamic Cooperative Path Planning with Hybrid Particle Swarm and Dynamic Window Algorithm in Three-Dimensional Terrain and Ocean Current Environment
by Bing Sun and Ziang Lv
Biomimetics 2025, 10(8), 536; https://doi.org/10.3390/biomimetics10080536 - 15 Aug 2025
Viewed by 492
Abstract
Aiming at the cooperative path-planning problem of multiple autonomous underwater vehicles in underwater three-dimensional terrain and dynamic ocean current environments, a hybrid algorithm based on the Improved Multi-Objective Particle Swarm Optimization (IMOPSO) and Dynamic Window (DWA) is proposed. The traditional particle swarm optimization [...] Read more.
Aiming at the cooperative path-planning problem of multiple autonomous underwater vehicles in underwater three-dimensional terrain and dynamic ocean current environments, a hybrid algorithm based on the Improved Multi-Objective Particle Swarm Optimization (IMOPSO) and Dynamic Window (DWA) is proposed. The traditional particle swarm optimization algorithm is prone to falling into local optimization in high-dimensional and complex marine environments. It is difficult to meet multiple constraint conditions, the particle distribution is uneven, and the adaptability to dynamic environments is poor. In response to these problems, a hybrid initialization method based on Chebyshev chaotic mapping, pre-iterative elimination, and boundary particle injection (CPB) is proposed, and the particle swarm optimization algorithm is improved by combining dynamic parameter adjustment and a hybrid perturbation mechanism. On this basis, the Dynamic Window Method (DWA) is introduced as the local path optimization module to achieve real-time avoidance of dynamic obstacles and rolling path correction, thereby constructing a globally and locally coupled hybrid path-planning framework. Finally, cubic spline interpolation is used to smooth the planned path. Considering factors such as path length, smoothness, deflection Angle, and ocean current kinetic energy loss, the dynamic penalty function is adopted to optimize the multi-AUV cooperative collision avoidance and terrain constraints. The simulation results show that the proposed algorithm can effectively plan the dynamic safe path planning of multiple AUVs. By comparing it with other algorithms, the efficiency and security of the proposed algorithm are verified, meeting the navigation requirements in the current environment. Experiments show that the IMOPSO–DWA hybrid algorithm reduces the path length by 15.5%, the threat penalty by 8.3%, and the total fitness by 3.2% compared with the traditional PSO algorithm. Full article
(This article belongs to the Special Issue Computer-Aided Biomimetics: 3rd Edition)
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15 pages, 4410 KB  
Article
Bio-Inspired Design of Mechanical Properties of Hybrid Topological Cellular Honeycomb Structures
by Yingqiu Sun, Fan Guo and Yangyang Liu
Biomimetics 2025, 10(8), 528; https://doi.org/10.3390/biomimetics10080528 - 12 Aug 2025
Viewed by 364
Abstract
Inspired by the evolutionary optimization of biological load-bearing systems, honeycomb structures are highly valued in applications involving impact protection and lightweight load-bearing due to their outstanding mechanical properties. This study introduces an interesting honeycomb structure known as the hybrid topological cellular honeycomb structure [...] Read more.
Inspired by the evolutionary optimization of biological load-bearing systems, honeycomb structures are highly valued in applications involving impact protection and lightweight load-bearing due to their outstanding mechanical properties. This study introduces an interesting honeycomb structure known as the hybrid topological cellular honeycomb structure (HTCHS), which integrates four distinctive topological cells. To effectively fabricate HTCHS samples, the research utilized a fused deposition modeling (FDM) process, employing polyethylene terephthalate glycol-modified (PETG) as the matrix material, successfully producing the HTCHS samples. A finite element simulation model for the HTCHS is created using LS-DYNA software(LS-DYNA R11.1.0 software), and its accuracy is confirmed through a comparative analysis of experimental and simulation results. The influence of the topological cell parameters (T1 to T4) on compressive energy absorption, specific energy absorption, and peak crushing force through parametric modeling is investigated. The mechanical properties of honeycomb structures vary depending on the cell parameters at different positions, and monotonically increasing the design parameters does not improve the energy absorption capacity of the HTCHS. To enhance the mechanical performance of the HTCHS, the initial periodic cell configurations are transformed into non-periodic designs. A discrete optimization design framework for local parameters of the HTCHS is established, integrating cell coding with the MOPSO algorithm. The feasibility of the optimization results is validated through experimental data, demonstrating that this study offers an effective technical solution for developing a novel generation of cellular honeycomb structures with customizable mechanical properties. Full article
(This article belongs to the Special Issue Computer-Aided Biomimetics: 3rd Edition)
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