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Ma Z, Zhao J, Yu L, Yan M, Liang L, Wu X, Xu M, Wang W, Yan S. A Review of Energy Supply for Biomachine Hybrid Robots. CYBORG AND BIONIC SYSTEMS 2023; 4:0053. [PMID: 37766796 PMCID: PMC10521967 DOI: 10.34133/cbsystems.0053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 09/02/2023] [Indexed: 09/29/2023] Open
Abstract
Biomachine hybrid robots have been proposed for important scenarios, such as wilderness rescue, ecological monitoring, and hazardous area surveying. The energy supply unit used to power the control backpack carried by these robots determines their future development and practical application. Current energy supply devices for control backpacks are mainly chemical batteries. To achieve self-powered devices, researchers have developed solar energy, bioenergy, biothermal energy, and biovibration energy harvesters. This review provides an overview of research in the development of chemical batteries and self-powered devices for biomachine hybrid robots. Various batteries for different biocarriers and the entry points for the design of self-powered devices are outlined in detail. Finally, an overview of the future challenges and possible directions for the development of energy supply devices used to biomachine hybrid robots is provided.
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Affiliation(s)
- Zhiyun Ma
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Jieliang Zhao
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Li Yu
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Mengdan Yan
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Lulu Liang
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Xiangbing Wu
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Mengdi Xu
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Wenzhong Wang
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, P. R. China
| | - Shaoze Yan
- Department of Mechanical Engineering, Tsinghua University, Beijing 100084, P. R. China
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Webster-Wood VA, Guix M, Xu NW, Behkam B, Sato H, Sarkar D, Sanchez S, Shimizu M, Parker KK. Biohybrid robots: recent progress, challenges, and perspectives. BIOINSPIRATION & BIOMIMETICS 2022; 18:015001. [PMID: 36265472 DOI: 10.1088/1748-3190/ac9c3b] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.
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Affiliation(s)
- Victoria A Webster-Wood
- Mechanical Engineering, Biomedical Engineering (by courtesy), McGowan Institute of Regenerative Medicine, Carnegie Mellon University, Pittsburgh, PA 15116, United States of America
| | - Maria Guix
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Baldiri-Reixac 10-12, 08028 Barcelona, Spain
- Departament de Ciència dels Materials i Química Física, Institut de Química Teòrica i Computacional Barcelona, Universitat de Barcelona, 08028 Barcelona, Spain
| | - Nicole W Xu
- Laboratories for Computational Physics and Fluid Dynamics, U.S. Naval Research Laboratory, Code 6041, Washington, DC, United States of America
| | - Bahareh Behkam
- Department of Mechanical Engineering, Institute for Critical Technology and Applied Science, Blacksburg, VA 24061, United States of America
| | - Hirotaka Sato
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 65 Nanyang Drive, Singapore, 637460, Singapore
| | - Deblina Sarkar
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
| | - Samuel Sanchez
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Baldiri-Reixac 10-12, 08028 Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Avda. Lluis Companys 23, 08010 Barcelona, Spain
| | - Masahiro Shimizu
- Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-machi, Toyonaka, Osaka, Japan
| | - Kevin Kit Parker
- Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States of America
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Cyborg Moth Flight Control Based on Fuzzy Deep Learning. MICROMACHINES 2022; 13:mi13040611. [PMID: 35457916 PMCID: PMC9030641 DOI: 10.3390/mi13040611] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 11/16/2022]
Abstract
Cyborg insect control methods can be divided into invasive methods and noninvasive methods. Compared to invasive methods, noninvasive methods are much easier to implement, but they are sensitive to complex and highly uncertain environments, for which classical control methods often have low control accuracy. In this paper, we present a noninvasive approach for cyborg moths stimulated by noninvasive ultraviolet (UV) rays. We propose a fuzzy deep learning method for cyborg moth flight control, which consists of a Behavior Learner and a Control Learner. The Behavior Learner is further divided into three hierarchies for learning the species’ common behaviors, group-specific behaviors, and individual-specific behaviors step by step to produce the expected flight parameters. The Control Learner learns how to set UV ray stimulation to make a moth exhibit the expected flight behaviors. Both the Control Learner and Behavior Learner (including its sub-learners) are constructed using a Pythagorean fuzzy denoising autoencoder model. Experimental results demonstrate that the proposed approach achieves significant performance advantages over the state-of-the-art approaches and obtains a high control success rate of over 83% for flight parameter control.
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Romano D, Donati E, Benelli G, Stefanini C. A review on animal-robot interaction: from bio-hybrid organisms to mixed societies. BIOLOGICAL CYBERNETICS 2019; 113:201-225. [PMID: 30430234 DOI: 10.1007/s00422-018-0787-5] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Accepted: 10/19/2018] [Indexed: 05/28/2023]
Abstract
Living organisms are far superior to state-of-the-art robots as they have evolved a wide number of capabilities that far encompass our most advanced technologies. The merging of biological and artificial world, both physically and cognitively, represents a new trend in robotics that provides promising prospects to revolutionize the paradigms of conventional bio-inspired design as well as biological research. In this review, a comprehensive definition of animal-robot interactive technologies is given. They can be at animal level, by augmenting physical or mental capabilities through an integrated technology, or at group level, in which real animals interact with robotic conspecifics. Furthermore, an overview of the current state of the art and the recent trends in this novel context is provided. Bio-hybrid organisms represent a promising research area allowing us to understand how a biological apparatus (e.g. muscular and/or neural) works, thanks to the interaction with the integrated technologies. Furthermore, by using artificial agents, it is possible to shed light on social behaviours characterizing mixed societies. The robots can be used to manipulate groups of living organisms to understand self-organization and the evolution of cooperative behaviour and communication.
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Affiliation(s)
- Donato Romano
- The BioRobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, PI, Italy.
| | - Elisa Donati
- The Institute of Neuroinformatics, University of Zurich/ETH, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Giovanni Benelli
- The BioRobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, PI, Italy
- Department of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124, Pisa, Italy
| | - Cesare Stefanini
- The BioRobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, PI, Italy
- HEIC Center, BME Department, Khalifa University, PO Box 127788, Abu Dhabi, UAE
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