Evolución de descriptores estadísticos de superficie de imágenes por programación genética para el reconocimiento de imágenes por CBIR: una primera aproximación

In the field of robotics, forward kinematics is an activity that allows finding a mathematical model for the resulting position in the final effector based on the robot joints position, a popular alternative for determining this model is defined by the Denavit Hartenberg convention, nevertheless, this method requires knowledge about linear algebra and three-dimensional spatial kinematics. Machine learning uses specific computational methodologies to solving similar problems in several areas, so it could be a viable answer for automatic determining of forwarding kinematics. In this work we propose the use of genetic programming as a machine learning algorithm for finding the forward kinematics of a 2 degrees of freedom robot, getting a satisfactory outcome obtaining a satisfactory result with blocks that describe the expected solution, validating the capacity of the genetic programming in order to validate this algorithm for later work with more complex robots.

show abstract

Evolución de descriptores estadísticos de superficie de imágenes por programación genética para el reconocimiento de imágenes por CBIR: una primera aproximación

Abstract: The steady increase of Internet in our society becomes more evident against the crude fact that more than a half of the internet infor-

Cited by 2 publications

References 6 publications

Evolution of Statistical Descriptors for the Image Recognition of Natural Sceneries by Means of Genetic Programming for CBIR Improvement

Evolution of Statistical Descriptors for the Image Recognition of Natural Sceneries by Means of Genetic Programming for CBIR Improvement

Forward Kinematics for 2 DOF Planar Robot using Linear Genetic Programming

Contact Info

Product

Resources

About