Bio-inspired navigation and exploration system for a hexapod robotic platform

This paper presents a biologically inspired system for guiding and controlling a virtual hexapod robot. Our navigation and exploration system is composed of subsystems that execute processes of path integration, action selection, actuator control and correction of the robot’s orientation. For the subsystem that serves the path integration function we modified an existing model of bio-inspired vector summation by adding the capability of performing online calculation. For the action selection subsystem that allows to switch between the behaviors of exploration, approaching a target and homing we modified an existing model of decision making for mediating social behaviors in mice. We added an additional circuit that projects a signal to the units representing each of the behaviors. In the case of the actuator control subsystem, the structure of a central pattern generator model that incorporates feedback and adaptation was used as the base for generating and transforming signals for the actuators. Finally, the orientation correction subsystem is a novel model that determines an error value from a desired and the current orientations. The proposed models were simulated as independent scripts and then implemented as ROS (Robot Operating System) nodes for controlling a robot simulation in Gazebo

• Autores: Pardo Cabrera, Josh; Rivero Ortega, Jesús David; Hurtado López, Julián; Ramírez Moreno, David Fernando
• Tipo de recurso: Article of journal
• Fecha de publicación: 2022
• Institución: Universidad Autónoma de Occidente
• Repositorio: RED: Repositorio Educativo Digital UAO
• Idioma: eng
• OAI Identifier: oai:red.uao.edu.co:10614/14721
• Acceso en línea: https://hdl.handle.net/10614/14721; https://red.uao.edu.co/
• Palabra clave: Neural networks; Path integration; Central pattern generator; Orientation correction; Vector summation; Bio-inspired robotics
• Rights: openAccess
• License: Derechos reservados - IOP Publishing, 2022