Authors:
César Ferreira
;
Pedro Silva
;
João André
;
Cristina P. Santos
and
Lino Costa
Affiliation:
University of Minho, Portugal
Keyword(s):
Biped Locomotion, CPG (Central Pattern Generator), Sensory Information.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Soft Computing
Abstract:
Generating biped locomotion in robotic platforms is hard. It has to deal with the complexity of the tasks which requires the synchronization of several joints, while monitoring stability. Further, it is also expected to deal with the great heterogeneity of existing platforms. The generation of adaptable locomotion further increases the complexity of the task.
In this paper, Genetic Programming (GP) is used as an automatic search method for motion primitives of a biped robot, that optimizes a given criterion. It does so by exploring and exploiting the capabilities and particularities of the platform.
In order to increase the adaptability of the achieved solutions, feedback pathways were directly included into the evolutionary process through sensory inputs.