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Biomimetics
Special Issues
Biologically Inspired Design and Control of Robots
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Biologically Inspired Design and Control of Robots

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Biomimetic Design, Constructions and Devices".

Deadline for manuscript submissions: closed (1 June 2023) | Viewed by 12200

Special Issue Editors

Prof. Dr. Peng Li

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China
Interests: miniature robot; morphing mechanism; mechanism design; metamorphous multirotor
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yantao Shen

E-Mail Website
Guest Editor
Department of Electrical and Biomedical Engineering, University of Nevada Reno, Reno, NV 89557, USA
Interests: biomimic robot design; snake robot control; shape morpihing mechanism
Special Issues, Collections and Topics in MDPI journals
Dr. Shan Luo

E-Mail Website
Guest Editor
Department of Engineering, King’s College London, London SE5 9NU, UK
Interests: visuo-tactile robotics; robot visuo-tactile sensing; multimodal robot perception; robot learning for grasping and manipulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The design and control of robots based on the biological mechanisms of plants and animals in nature is a key theme in robotics research. As a discipline arising from the fusion of new materials, mechanical design, motor control, and AI algorithms, biomimetics provides unique inspiration for advancing the development of cognitive and collaborative functionalities, as well as improving the dexterous and versatile manipulation capabilities of robots.

The aim of this Special Issue is to collect contributions on the design and control of bionic robots. By covering issues from biomimetic materials to biomimetic mechanical design, brain-inspired robotic cognition-related  learning, and bioinspired control, our Special Issue provides an updated view of the status quo and perspectives in a rapidly growing field of the design and control of bionic robots. The present collection of papers, taking advantage of the open access format, is expected to provide a paradigm of the power of biomimetic approaches for discovering new important research avenues and for innovative solutions in the design and control of bionic robots.

To further its aims of combining basic research and applications, this Special Issue is divided into two main focuses:

  1. Design, covering topics such as: the mechanical design of biomimetic robots; intelligent sensors (e.g., vision, tactile, etc.) for perception and exploration; new materials; applications of biomimetic robotics in industry, e.g., manipulation, robot assisted surgery.
  2. Control, including bioinspired robotic learning and control, intelligent learning methods from a biomimetic view; computational neuroscience of perception and action; bionic motion control; advanced multi-modal sensing information fusion;

We believe that this initiative will fill an important gap in biomimetic  technologies.

Dr. Peng Li
Prof. Dr. Yantao Shen
Dr. Shan Luo
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

  • mechanical design
  • biomimetic robots
  • intelligent sensors
  • new materials
  • bioinspired robotic learning and control
  • intelligent learning methods
  • computational neuroscience
  • advanced multimodal sensing information fusion

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

Published Papers (5 papers)

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Research

22 pages, 41837 KiB  
Article
Design, Control, and Validation of a Symmetrical Hip and Straight-Legged Vertically-Compliant Bipedal Robot
by Jun Tang, Yudi Zhu, Wencong Gan, Haiming Mou, Jie Leng, Qingdu Li, Zhiqiang Yu and Jianwei Zhang
Biomimetics 2023, 8(4), 340; https://doi.org/10.3390/biomimetics8040340 - 1 Aug 2023
Cited by 3 | Viewed by 2197
Abstract
This paper presents the development, modeling, and control of L03, an underactuated 3D bipedal robot with symmetrical hips and straight legs. This innovative design requires only five actuators, two for the legs and three for the hips. This paper is divided into three [...] Read more.
This paper presents the development, modeling, and control of L03, an underactuated 3D bipedal robot with symmetrical hips and straight legs. This innovative design requires only five actuators, two for the legs and three for the hips. This paper is divided into three parts: (1) mechanism design and kinematic analysis; (2) trajectory planning for the center of mass and foot landing points based on the Divergent Component of Motion (DCM), enabling lateral and forward walking capabilities for the robot; and (3) gait stability analysis through prototype experiments. The primary focus of this study is to explore the application of underactuated symmetrical designs and determine the number of motors required to achieve omnidirectional movement of a bipedal robot. Our simulation and experimental results demonstrate that L03 achieves simple walking with a stable and consistent gait. Due to its lightweight construction, low leg inertia, and straight-legged design, L03 can achieve ground perception and gentle ground contact without the need for force sensors. Compared to existing bipedal robots, L03 closely adheres to the characteristics of the linear inverted pendulum model, making it an invaluable platform for future algorithm research. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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13 pages, 50060 KiB  
Article
Opponent Hitting Behavior Prediction and Ball Location Control for a Table Tennis Robot
by Yunfeng Ji, Yue Mao, Fangfei Suo, Xiaoyi Hu, Yunfeng Hou and Ye Yuan
Biomimetics 2023, 8(2), 229; https://doi.org/10.3390/biomimetics8020229 - 29 May 2023
Cited by 4 | Viewed by 2224
Abstract
The hitting position and velocity control for table tennis robots have been investigated widely in the literature. However, most of the studies conducted do not consider the opponent’s hitting behaviors, which may reduce hitting accuracy. This paper proposes a new table tennis robot [...] Read more.
The hitting position and velocity control for table tennis robots have been investigated widely in the literature. However, most of the studies conducted do not consider the opponent’s hitting behaviors, which may reduce hitting accuracy. This paper proposes a new table tennis robot framework that returns the ball based on the opponent’s hitting behaviors. Specifically, we classify the opponent’s hitting behaviors into four categories: forehand attacking, forehand rubbing, backhand attacking, and backhand rubbing. A tailor-made mechanical structure that consists of a robot arm and a two-dimensional slide rail is developed such that the robot can reach large workspaces. Additionally, a visual module is incorporated to enable the robot to capture opponent motion sequences. Based on the opponent’s hitting behaviors and the predicted ball trajectory, smooth and stable control of the robot’s hitting motion can be obtained by applying quintic polynomial trajectory planning. Moreover, a motion control strategy is devised for the robot to return the ball to the desired location. Extensive experimental results are presented to demonstrate the effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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17 pages, 3117 KiB  
Article
Design, Modeling, and Control of a New Multi-Motion Mobile Robot Based on Spoked Mecanum Wheels
by Jie Leng, Haiming Mou, Jun Tang, Qingdu Li and Jianwei Zhang
Biomimetics 2023, 8(2), 183; https://doi.org/10.3390/biomimetics8020183 - 28 Apr 2023
Cited by 5 | Viewed by 2439
Abstract
This paper presents an exciting and meaningful design to make mobile robots capable of adapting to various terrains. We designed a relatively simple and novel composite motion mechanism called the flexible spoked mecanum (FSM) wheel and created a mobile robot, LZ-1, with multiple [...] Read more.
This paper presents an exciting and meaningful design to make mobile robots capable of adapting to various terrains. We designed a relatively simple and novel composite motion mechanism called the flexible spoked mecanum (FSM) wheel and created a mobile robot, LZ-1, with multiple motion modes based on the FSM wheel. Based on the motion analysis of the FSM wheel, we designed an omnidirectional motion mode for this robot, allowing it to move flexibly in all directions and successfully traverse rugged terrains. In addition, we designed a crawl motion mode for this robot, which can climb stairs effectively. We used a multilayer control method to move the robot according to the designed motion modes. Multiple experiments showed that these two motion modes for the robot are effective on various terrains. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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16 pages, 12712 KiB  
Article
A Recognition Method for Soft Objects Based on the Fusion of Vision and Haptics
by Teng Sun, Zhe Zhang, Zhonghua Miao and Wen Zhang
Biomimetics 2023, 8(1), 86; https://doi.org/10.3390/biomimetics8010086 - 20 Feb 2023
Viewed by 2318
Abstract
For humans and animals to recognise an object, the integration of multiple sensing methods is essential when one sensing modality is only able to acquire limited information. Among the many sensing modalities, vision has been intensively studied and proven to have superior performance [...] Read more.
For humans and animals to recognise an object, the integration of multiple sensing methods is essential when one sensing modality is only able to acquire limited information. Among the many sensing modalities, vision has been intensively studied and proven to have superior performance for many problems. Nevertheless, there are many problems which are difficult to solve by solitary vision, such as in a dark environment or for objects with a similar outlook but different inclusions. Haptic sensing is another commonly used means of perception, which can provide local contact information and physical features that are difficult to obtain by vision. Therefore, the fusion of vision and touch is beneficial to improve the robustness of object perception. To address this, an end-to-end visual–haptic fusion perceptual method has been proposed. In particular, the YOLO deep network is used to extract vision features, while haptic explorations are used to extract haptic features. Then, visual and haptic features are aggregated using a graph convolutional network, and the object is recognised based on a multi-layer perceptron. Experimental results show that the proposed method excels in distinguishing soft objects that have similar appearance but varied interior fillers, comparing a simple convolutional network and a Bayesian filter. The resultant average recognition accuracy was improved to 0.95 from vision only (mAP is 0.502). Moreover, the extracted physical features could be further used for manipulation tasks targeting soft objects. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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18 pages, 5484 KiB  
Article
Bionic Path Planning Fusing Episodic Memory Based on RatSLAM
by Shumei Yu, Haidong Xu, Chong Wu, Xin Jiang, Rongchuan Sun and Lining Sun
Biomimetics 2023, 8(1), 59; https://doi.org/10.3390/biomimetics8010059 - 1 Feb 2023
Cited by 3 | Viewed by 1908
Abstract
Inspired by rodents’ ability to navigate freely in a given space, bionavigation systems provide alternatives to traditional probabilistic solutions. This paper proposed a bionic path planning method based on RatSLAM to provide a novel viewpoint for robots to make a more flexible and [...] Read more.
Inspired by rodents’ ability to navigate freely in a given space, bionavigation systems provide alternatives to traditional probabilistic solutions. This paper proposed a bionic path planning method based on RatSLAM to provide a novel viewpoint for robots to make a more flexible and intelligent navigation scheme. A neural network fusing historic episodic memory was proposed to improve the connectivity of the episodic cognitive map. It is biomimetically important to generate an episodic cognitive map and establish a one-to-one correspondence between the events generated by episodic memory and the visual template of RatSLAM. The episodic cognitive map can be improved by imitating the rodents’ behavior of memory fusion to produce better path planning results. The experimental results of different scenarios illustrate that the proposed method identified the connectivity between way points, optimized the result of path planning, and improved the flexibility of the system. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots)
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