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...
- 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
| Summary: | 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 |
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