Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot

The aim of this work is to propose bio-inspired neural networks for decision-making mechanisms and modulation of motor control of an automaton. In this work, we have adapted and applied cortical synaptic circuits, such as short-term memory circuits, winner-take-all (WTA) class competitive neural net...

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Autores:
Guerrero-Criollo, Roberto José
Castaño-López, Jason Alejandro
Hurtado López, Julián
Ramírez Moreno, David Fernando
Tipo de recurso:
Article of journal
Fecha de publicación:
2023
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/15545
Acceso en línea:
https://hdl.handle.net/10614/15545
https://red.uao.edu.co/
Palabra clave:
Bio-inspired neural network
Neuromodulation network
Adaptation stage
Signal processing
Dierential robot
Exploration behavior
Automa
Rights
openAccess
License
Derechos reservados - Frontiers Media S.A., 2023
id REPOUAO2_f21bafcad150eb0cdcb3300a7a73170c
oai_identifier_str oai:red.uao.edu.co:10614/15545
network_acronym_str REPOUAO2
network_name_str RED: Repositorio Educativo Digital UAO
repository_id_str
dc.title.eng.fl_str_mv Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
title Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
spellingShingle Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
Bio-inspired neural network
Neuromodulation network
Adaptation stage
Signal processing
Dierential robot
Exploration behavior
Automa
title_short Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
title_full Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
title_fullStr Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
title_full_unstemmed Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
title_sort Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot
dc.creator.fl_str_mv Guerrero-Criollo, Roberto José
Castaño-López, Jason Alejandro
Hurtado López, Julián
Ramírez Moreno, David Fernando
dc.contributor.author.none.fl_str_mv Guerrero-Criollo, Roberto José
Castaño-López, Jason Alejandro
Hurtado López, Julián
Ramírez Moreno, David Fernando
dc.subject.proposal.eng.fl_str_mv Bio-inspired neural network
Neuromodulation network
Adaptation stage
Signal processing
Dierential robot
Exploration behavior
Automa
topic Bio-inspired neural network
Neuromodulation network
Adaptation stage
Signal processing
Dierential robot
Exploration behavior
Automa
description The aim of this work is to propose bio-inspired neural networks for decision-making mechanisms and modulation of motor control of an automaton. In this work, we have adapted and applied cortical synaptic circuits, such as short-term memory circuits, winner-take-all (WTA) class competitive neural networks, modulation neural networks, and nonlinear oscillation circuits, in order to make the automaton able to avoid obstacles and explore simulated and real environments. The performance achieved by using biologically inspired neural networks to solve the task at hand is similar to that of several works mentioned in the specialized literature. Furthermore, this work contributed to bridging the fields of computational neuroscience and robotics
publishDate 2023
dc.date.issued.none.fl_str_mv 2023-02-03
dc.date.accessioned.none.fl_str_mv 2024-04-17T16:21:07Z
dc.date.available.none.fl_str_mv 2024-04-17T16:21:07Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.citation.spa.fl_str_mv Guerrero-Criollo, R. J.; Castaño-López, J. A.; Hurtado-López, J.; o Ramírez-Moreno, D.F. (2023). Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot. Frontiers in Neurorobotics. p.p. 1-16. DOI 10.3389/fnbot.2023.1078074
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/10614/15545
dc.identifier.doi.none.fl_str_mv DOI 10.3389/fnbot.2023.1078074
dc.identifier.eissn.spa.fl_str_mv 1662-5218
dc.identifier.instname.spa.fl_str_mv Universidad Autónoma de Occidente
dc.identifier.reponame.spa.fl_str_mv Respositorio Educativo Digital UAO
dc.identifier.repourl.none.fl_str_mv https://red.uao.edu.co/
identifier_str_mv Guerrero-Criollo, R. J.; Castaño-López, J. A.; Hurtado-López, J.; o Ramírez-Moreno, D.F. (2023). Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot. Frontiers in Neurorobotics. p.p. 1-16. DOI 10.3389/fnbot.2023.1078074
DOI 10.3389/fnbot.2023.1078074
1662-5218
Universidad Autónoma de Occidente
Respositorio Educativo Digital UAO
url https://hdl.handle.net/10614/15545
https://red.uao.edu.co/
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.citationendpage.none.fl_str_mv 16
dc.relation.citationstartpage.none.fl_str_mv 1
dc.relation.ispartofjournal.eng.fl_str_mv Frontiers in neurorobotics
dc.relation.references.none.fl_str_mv Cao, Z., Cheng, L., Zhou, C., Gu, N., Wang, X., and Tan, M. (2015). Spiking neural network-based target tracking control for autonomous mobile robots. Neural Comput. Appl. 26, 1839–1847. doi: 10.1007/s00521-015-1848-5
Foundation, O. S. R. (2014). Gazebo. Available online at: http://gazebosim.org/
Guerrero-Criollo, R. J., Castaño-López, J. A., Díaz-Cuchala, R. E., David Rozo- Giraldo, Y., and Ramirez-Moreno, D. F. (2022). “Design and simulation of a bio-inspired neural network for the motor control of a mobile automaton,” in 2022 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI) (Cali: IEEE), 1–6.
Héricé, C., Khalil, R., Moftah, M., Boraud, T., Guthrie, M., and Garenne, A. (2016). Decision making under uncertainty in a spiking neural network model of the basal ganglia. J. Integr. Neurosci. 15, 515–53. doi: 10.1142/S021963521650028X
Hikosaka, O., Ghazizadeh, A., Griggs, W., and Amita, H. (2018). Parallel basal ganglia circuits for decision making. J. Neural Transm. 125, 515–529. doi: 10.1007/s00702-017-1691-1
Hurtado-López, J., and Ramirez-Moreno, D. F. (2019). Dynamics of a neural circuit that mediates social and nonsocial behaviors. Int. J. Bifurcat. Chaos 29, 1950138. doi: 10.1142/S0218127419501384
Hurtado-López, J., Ramirez-Moreno, D. F., and Sejnowski, T. J. (2017). Decisionmaking neural circuits mediating social behaviors. J. Comput. Neurosci. 43, 127–142. doi: 10.1007/s10827-017-0654-8
Liu, J., Hua, Y., Yang, R., Luo, Y., Lu, H., Wang, Y., et al. (2022). Bio-inspired autonomous learning algorithm with application to mobile robot obstacle avoidance. Front. Neurosci. 16, 905596. doi: 10.3389/fnins.2022.905596
Lobov, S. A., Mikhaylov, A. N., Shamshin, M., Makarov, V. A., and Kazantsev, V. B. (2020). Spatial properties of stdp in a self-learning spiking neural network enable controlling a mobile robot. Front. Neurosci. 14, 88. doi: 10.3389/fnins.2020.00088
Macktoobian, M., and Khataminejad, A. T. (2016). On the formal development of behavioral reactive agents: a systematic braitenberg-vehicle approach. arXiv[Preprint].arXiv:1612.03979. doi: 10.48550/arXiv.1612.03979
Miguel-Blanco, A., and Manoonpong, P. (2020). General distributed neural control and sensory adaptation for self-organized locomotion and fast adaptation to damage of walking robots. Front. Neural Circ. 14, 46. doi: 10.3389/fncir.2020.00046
Ngamkajornwiwat, P., Homchanthanakul, J., Teerakittikul, P., and Manoonpong, P. (2020). Bio-inspired adaptive locomotion control system for online adaptation of a walking robot on complex terrains. IEEE Access 8, 91587–91602. doi: 10.1109/ACCESS.2020.2992794
Open Source Robotics Foundation, I. (2020). Turtlebot3. Available online at: http:// wiki.ros.org/Robots/TurtleBot
Pardo-Cabrera, J., Rivero-Ortega, J. D., Hurtado-López, J., and Ramírez-Moreno, D. F. (2022). Bio-inspired navigation and exploration system for a hexapod robotic platform. Eng. Res. Express 4, 025019. doi: 10.1088/2631-8695/ac6bde
Ramirez-Moreno, D., and Hurtado-Lopez, J. (2014). Modelamiento Y Simulación De Circuitos Sipnáticos Sensoriomotores: Introducción a la Neurobiología Computacional. Calle: Universidad Autónoma de Occidente.
Ramirez-Moreno, D. F., and Sejnowski, T. J. (2012). A computational model for the modulation of the prepulse inhibition of the acoustic startle reflex. Biol. Cybern. 106, 169–176. doi: 10.1007/s00422-012-0485-7
Robotics, O. (2021). Ros (robot operation system). Available online at: https://www. ros.org/
Robotis (2022). Turtlebot3 specifications. Available online at: https://emanual.robotis. com/docs/en/platform/turtlebot3/features/
Shim, M. S., and Li, P. (2017). “Biologically inspired reinforcement learning for mobile robot collision avoidance,” in 2017 International Joint Conference on Neural Networks (IJCNN), 3098–3105. doi: 10.1109/IJCNN.2017.7966242. Available online at: https://ieeexplore.ieee.org/document/7966242
Suzuki, S., Kano, T., Ijspeert, A. J., and Ishiguro, A. (2021). Sprawling quadruped robot driven by decentralized control with cross-coupled sensory feedback between legs and trunk. Front. Neurorobot. 14, 607455. doi: 10.3389/fnbot.2020.607455
Thor, M., Strohmer, B., and Manoonpong, P. (2021). Locomotion control with frequency and motor pattern adaptations. Front. Neural Circ. 15, 743888. doi: 10.3389/fncir.2021.743888
Wei, H., Bu, Y., and Dai, D. (2017). A decision-making model based on a spiking neural circuit and synaptic plasticity. Cogn. Neurodyn. 11, 415–431. doi: 10.1007/s11571-017-9436-2
Wilson, H. R., and Cowan, J. D. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 12, 1–24. doi: 10.1016/S0006-3495(72)86068-5
Yan, Z., Fabresse, L., Laval, J., and Bouraqadi, N. (2015). “Metrics for performance benchmarking of multi-robot exploration,” in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Hamburg: IEEE), 3407–3414.
Zahra, O., Tolu, S., Zhou, P., Duan, A., and Navarro-Alarcon, D. (2022). A bio-inspired mechanism for learning robot motion from mirrored human demonstrations. Front. Neurorobot. 16, 826410. doi: 10.3389/fnbot.2022.826410
Zhao, F., Zeng, Y., Guo, A., Su, H., and Xu, B. (2020). A neural algorithm for drosophila linear and nonlinear decision-making. Sci. Rep. 10, 1–16. doi: 10.1038/s41598-020-75628-y
dc.rights.spa.fl_str_mv Derechos reservados - Frontiers Media S.A., 2023
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spelling Guerrero-Criollo, Roberto JoséCastaño-López, Jason AlejandroHurtado López, Juliánvirtual::5333-1Ramírez Moreno, David Fernandovirtual::5334-12024-04-17T16:21:07Z2024-04-17T16:21:07Z2023-02-03Guerrero-Criollo, R. J.; Castaño-López, J. A.; Hurtado-López, J.; o Ramírez-Moreno, D.F. (2023). Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot. Frontiers in Neurorobotics. p.p. 1-16. DOI 10.3389/fnbot.2023.1078074https://hdl.handle.net/10614/15545DOI 10.3389/fnbot.2023.10780741662-5218Universidad Autónoma de OccidenteRespositorio Educativo Digital UAOhttps://red.uao.edu.co/The aim of this work is to propose bio-inspired neural networks for decision-making mechanisms and modulation of motor control of an automaton. In this work, we have adapted and applied cortical synaptic circuits, such as short-term memory circuits, winner-take-all (WTA) class competitive neural networks, modulation neural networks, and nonlinear oscillation circuits, in order to make the automaton able to avoid obstacles and explore simulated and real environments. The performance achieved by using biologically inspired neural networks to solve the task at hand is similar to that of several works mentioned in the specialized literature. Furthermore, this work contributed to bridging the fields of computational neuroscience and robotics16 páginasapplication/pdfengFrontiers Media S.A.SwitzerlandDerechos reservados - Frontiers Media S.A., 2023https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robotArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85161Frontiers in neuroroboticsCao, Z., Cheng, L., Zhou, C., Gu, N., Wang, X., and Tan, M. (2015). Spiking neural network-based target tracking control for autonomous mobile robots. Neural Comput. Appl. 26, 1839–1847. doi: 10.1007/s00521-015-1848-5Foundation, O. S. R. (2014). Gazebo. Available online at: http://gazebosim.org/Guerrero-Criollo, R. J., Castaño-López, J. A., Díaz-Cuchala, R. E., David Rozo- Giraldo, Y., and Ramirez-Moreno, D. F. (2022). “Design and simulation of a bio-inspired neural network for the motor control of a mobile automaton,” in 2022 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI) (Cali: IEEE), 1–6.Héricé, C., Khalil, R., Moftah, M., Boraud, T., Guthrie, M., and Garenne, A. (2016). Decision making under uncertainty in a spiking neural network model of the basal ganglia. J. Integr. Neurosci. 15, 515–53. doi: 10.1142/S021963521650028XHikosaka, O., Ghazizadeh, A., Griggs, W., and Amita, H. (2018). Parallel basal ganglia circuits for decision making. J. Neural Transm. 125, 515–529. doi: 10.1007/s00702-017-1691-1Hurtado-López, J., and Ramirez-Moreno, D. F. (2019). Dynamics of a neural circuit that mediates social and nonsocial behaviors. Int. J. Bifurcat. Chaos 29, 1950138. doi: 10.1142/S0218127419501384Hurtado-López, J., Ramirez-Moreno, D. F., and Sejnowski, T. J. (2017). Decisionmaking neural circuits mediating social behaviors. J. Comput. Neurosci. 43, 127–142. doi: 10.1007/s10827-017-0654-8Liu, J., Hua, Y., Yang, R., Luo, Y., Lu, H., Wang, Y., et al. (2022). Bio-inspired autonomous learning algorithm with application to mobile robot obstacle avoidance. Front. Neurosci. 16, 905596. doi: 10.3389/fnins.2022.905596Lobov, S. A., Mikhaylov, A. N., Shamshin, M., Makarov, V. A., and Kazantsev, V. B. (2020). Spatial properties of stdp in a self-learning spiking neural network enable controlling a mobile robot. Front. Neurosci. 14, 88. doi: 10.3389/fnins.2020.00088Macktoobian, M., and Khataminejad, A. T. (2016). On the formal development of behavioral reactive agents: a systematic braitenberg-vehicle approach. arXiv[Preprint].arXiv:1612.03979. doi: 10.48550/arXiv.1612.03979Miguel-Blanco, A., and Manoonpong, P. (2020). General distributed neural control and sensory adaptation for self-organized locomotion and fast adaptation to damage of walking robots. Front. Neural Circ. 14, 46. doi: 10.3389/fncir.2020.00046Ngamkajornwiwat, P., Homchanthanakul, J., Teerakittikul, P., and Manoonpong, P. (2020). Bio-inspired adaptive locomotion control system for online adaptation of a walking robot on complex terrains. IEEE Access 8, 91587–91602. doi: 10.1109/ACCESS.2020.2992794Open Source Robotics Foundation, I. (2020). Turtlebot3. Available online at: http:// wiki.ros.org/Robots/TurtleBotPardo-Cabrera, J., Rivero-Ortega, J. D., Hurtado-López, J., and Ramírez-Moreno, D. F. (2022). Bio-inspired navigation and exploration system for a hexapod robotic platform. Eng. Res. Express 4, 025019. doi: 10.1088/2631-8695/ac6bdeRamirez-Moreno, D., and Hurtado-Lopez, J. (2014). Modelamiento Y Simulación De Circuitos Sipnáticos Sensoriomotores: Introducción a la Neurobiología Computacional. Calle: Universidad Autónoma de Occidente.Ramirez-Moreno, D. F., and Sejnowski, T. J. (2012). A computational model for the modulation of the prepulse inhibition of the acoustic startle reflex. Biol. Cybern. 106, 169–176. doi: 10.1007/s00422-012-0485-7Robotics, O. (2021). Ros (robot operation system). Available online at: https://www. ros.org/Robotis (2022). Turtlebot3 specifications. Available online at: https://emanual.robotis. com/docs/en/platform/turtlebot3/features/Shim, M. S., and Li, P. (2017). “Biologically inspired reinforcement learning for mobile robot collision avoidance,” in 2017 International Joint Conference on Neural Networks (IJCNN), 3098–3105. doi: 10.1109/IJCNN.2017.7966242. Available online at: https://ieeexplore.ieee.org/document/7966242Suzuki, S., Kano, T., Ijspeert, A. J., and Ishiguro, A. (2021). Sprawling quadruped robot driven by decentralized control with cross-coupled sensory feedback between legs and trunk. Front. Neurorobot. 14, 607455. doi: 10.3389/fnbot.2020.607455Thor, M., Strohmer, B., and Manoonpong, P. (2021). Locomotion control with frequency and motor pattern adaptations. Front. Neural Circ. 15, 743888. doi: 10.3389/fncir.2021.743888Wei, H., Bu, Y., and Dai, D. (2017). A decision-making model based on a spiking neural circuit and synaptic plasticity. Cogn. Neurodyn. 11, 415–431. doi: 10.1007/s11571-017-9436-2Wilson, H. R., and Cowan, J. D. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 12, 1–24. doi: 10.1016/S0006-3495(72)86068-5Yan, Z., Fabresse, L., Laval, J., and Bouraqadi, N. (2015). “Metrics for performance benchmarking of multi-robot exploration,” in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Hamburg: IEEE), 3407–3414.Zahra, O., Tolu, S., Zhou, P., Duan, A., and Navarro-Alarcon, D. (2022). A bio-inspired mechanism for learning robot motion from mirrored human demonstrations. Front. Neurorobot. 16, 826410. doi: 10.3389/fnbot.2022.826410Zhao, F., Zeng, Y., Guo, A., Su, H., and Xu, B. (2020). A neural algorithm for drosophila linear and nonlinear decision-making. Sci. Rep. 10, 1–16. doi: 10.1038/s41598-020-75628-yBio-inspired neural networkNeuromodulation networkAdaptation stageSignal processingDierential robotExploration behaviorAutomaComunidad generalPublication77636374-92e2-4d63-9b49-bdb0a2ea1182virtual::5333-161e20236-82c5-4dcc-b05c-0eaa9ac06b11virtual::5334-177636374-92e2-4d63-9b49-bdb0a2ea1182virtual::5333-161e20236-82c5-4dcc-b05c-0eaa9ac06b11virtual::5334-1https://scholar.google.com/citations?user=7Pqx31YAAAAJ&hl=esvirtual::5333-1https://scholar.google.com/citations?user=RTce1fkAAAAJ&hl=esvirtual::5334-10000-0002-3773-0598virtual::5333-10000-0003-2372-3554virtual::5334-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000828963virtual::5333-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000353744virtual::5334-1ORIGINALBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdfBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdfArchivo texto completo del artículo de revista, PDFapplication/pdf3170663https://red.uao.edu.co/bitstreams/285a8ab6-bf48-4156-a67e-dfa071693271/downloadbd3eeaf7e4bf6285ddab128e404e724cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81672https://red.uao.edu.co/bitstreams/d3a7b3c5-d245-4712-a66b-28e7d880b148/download6987b791264a2b5525252450f99b10d1MD52TEXTBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdf.txtBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdf.txtExtracted texttext/plain60051https://red.uao.edu.co/bitstreams/e76fea4c-fd02-4c4c-bb82-43d2a95c352b/download9075a831c1736b669e5b2005fbf6cdddMD53THUMBNAILBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdf.jpgBio_inspired_neural_networks_for_decision_making_mechanisms_and_neuromodulation_for_motor_control_in_a_differential_robot.pdf.jpgGenerated Thumbnailimage/jpeg12240https://red.uao.edu.co/bitstreams/2670e181-6e54-4444-acf7-c75f96c3a1e9/downloaddcfef6ba3a12088dd948ef56aaa998bcMD5410614/15545oai:red.uao.edu.co:10614/155452024-04-18 03:01:56.826https://creativecommons.org/licenses/by-nc-nd/4.0/Derechos reservados - Frontiers Media S.A., 2023open.accesshttps://red.uao.edu.coRepositorio Digital Universidad Autonoma de Occidenterepositorio@uao.edu.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