Hexápodo de posición iterada especializado en la espeleología (x-cabot). Fase 2

Abstract

Este artículo presenta el diseño de un banco de pruebas enfocado al control de las piernas de un robot hexápodo, que permite estudiar las características del robot y obtener algunos comportamientos primarios, ya sean mecánicos, eléctricos o de programación. De esta forma, se propone una estructura de banco de pruebas para validar los sistemas de control, desempeño e identificación de acuerdo con los esfuerzos que ejerce cada uno de los componentes del hexápodo y también obtener una visión detallada de su desempeño en ambientes estructurados y no estructurados con el fin de corregir sus posibles limitaciones para que en su implementación pueda tener coherencia en respuesta a las tareas que se plantean.

This article presents the design of a test bench focused on the control of the legs of a hexapod robot, which allows studying the characteristics of the robot and obtaining some primary behaviors, whether mechanical, electrical or programming. In this way, a test bench structure is proposed to validate the control, performance and identification systems according to the efforts exerted by each of the components of the hexapod and also obtain a detailed view of their performance in structured environments and unstructured in order to correct its possible limitations so that in its implementation it can have coherence in response to the tasks that are posed. The results show the development of the test bench in which different types of legs were implemented which were considered the study of the mathematical model of direct kinematics and the selection of materials. For this reason, it is obtained that the best leg was the carbon fiber, since it has a very high safety coefficient, and it is very difficult for a fracture to occur when implementing it in the prototype, it is also chosen for its weight in comparison to other materials, since its characteristics have a lower structure density and high elasticity, it supports more axial loads than the other legs, even when subjected to intensive work. Finally, it is validated that the robot's performance in locomotion actions, basing this validation on the interpretation of the parameters captured by an optical sensor arranged for this task that generates the monitoring of movements in a controlled environment free of obstacles