Version 1
: Received: 2 April 2024 / Approved: 3 April 2024 / Online: 3 April 2024 (08:34:47 CEST)
How to cite:
Hu, K.-.; Zhang, Y.; Ding, F.; Yang, D.; Yu, Y.; Yu, Y.; Wang, Q.; Baoyin, H. Innate Orientating Behavior of a Multi-legged Robot Driven by the Neural Circuits of C. elegans. Preprints2024, 2024040270. https://doi.org/10.20944/preprints202404.0270.v1
Hu, K.-.; Zhang, Y.; Ding, F.; Yang, D.; Yu, Y.; Yu, Y.; Wang, Q.; Baoyin, H. Innate Orientating Behavior of a Multi-legged Robot Driven by the Neural Circuits of C. elegans. Preprints 2024, 2024040270. https://doi.org/10.20944/preprints202404.0270.v1
Hu, K.-.; Zhang, Y.; Ding, F.; Yang, D.; Yu, Y.; Yu, Y.; Wang, Q.; Baoyin, H. Innate Orientating Behavior of a Multi-legged Robot Driven by the Neural Circuits of C. elegans. Preprints2024, 2024040270. https://doi.org/10.20944/preprints202404.0270.v1
APA Style
Hu, K.-., Zhang, Y., Ding, F., Yang, D., Yu, Y., Yu, Y., Wang, Q., & Baoyin, H. (2024). Innate Orientating Behavior of a Multi-legged Robot Driven by the Neural Circuits of <em>C. elegans</em>. Preprints. https://doi.org/10.20944/preprints202404.0270.v1
Chicago/Turabian Style
Hu, K.-., Qingyun Wang and Hexi Baoyin. 2024 "Innate Orientating Behavior of a Multi-legged Robot Driven by the Neural Circuits of <em>C. elegans</em>" Preprints. https://doi.org/10.20944/preprints202404.0270.v1
Abstract
Biological neural network (BNN) is the core brain for creature to accomplish its intelligent behaviors through unique network structure and mechanisms. It also inspires controlling human-designed autonomous agents including robots to generate more advanced intelligent behaviors by mimicking the neural control mechanism of creatures at a deeper and more interactive level. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of cellular synapse. The neural network simulation integrates computational programming and visualization of neurons and synapse connections of C. elegans, containing the specific controllable circuits summarization with their dynamic characteristics within the whole network. To illustrate its particular intelligent control capability in terms of robotics, we introduce the first innovative methodology for applying the BNN model to a 12-legged robot’s movement control based on the established numerical simulation platforms. We accomplished and designed two methods and corresponding encoding processes, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of BNN. Both simulation and experiment results indicate that the robot exhibits stronger autonomy and more intelligent moving performance under the control of BNN. We then summarized the contributions for digitalizing the C. elegans’ whole-brain neural network in real-time and utilizing it to control robot in a closed loop to validate its advanced intelligence control ability in terms of a scientific robot.
Keywords
Biological Neural Network; C. elegans, Neural Dynamics; Computing Model of Whole-brain Neural Network; Bionic Robot Intelligent Control
Subject
Biology and Life Sciences, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
