Feed-forward Controller Using DeNOC Methodology for a Wheeled Humanoid Robot

Most standard controllers for high degrees of freedom (dof) robots are prone to consume large quantity of energy and computational time. Humanoid high dof robots are mostly controlled using model-based controllers due to their better accuracy relatively to other controllers. This paper presents a model-based feed-forward control strategy incorporating a Decoupled Natural Orthogonal Complement (DeNOC) methodology for a wheeled humanoid robot. For a 15 dof humanoid robot with a wheeled base, performance of the proposed feed-forward controller was compared with a traditional feed-forward controller. A steady state error, settling time and energy consumption during a task performance were compared to determine an efficiency of the proposed controller. A simulation study and an experimental validation were used to evaluate results of the performance analysis.