This paper deals with the design of the full size humanoid robot TEO, an improved version of its predecessor RH-1. The whole platform is conceived under the premise of high efficiency in terms of energy consumption and optimization. We will focus mainly on the electromechanical structure of the lower part of the prototype, which is the main component demanding energy during motion. The dimensions and weight of the robotic platform, together with its link configuration and rigidity, will be optimized. Experimental results are presented to show the validity of the design.
Efficient methods have so far been proposed for planning dynamically stable walking pattern for humanoid robots. However, to guarantee that the reference joint trajectory will produce a safe movement despite modeling errors and perturbations, a stabilizer needs to be implemented on the robot. Though this stabilizer constitutes an essential part of the control strategy of most advanced humanoid platform, it is usually not open-source and dedicated to the own robot characteristics. The goal of this paper is to propose a general and practical strategy for designing a stabilizer for jointposition controlled humanoid robots. The proposed method is based on a double inverted pendulum model and a decoupling approach thanks to which the position of the ZMP and the center of gravity can be controlled independently through the regulation of the ankle and hip joints. The stabilizer generates the expected stabilizing torques from the admissible joint position input. The resulting control algorithm is fast and can be easily executed on the robot. This algorithm was successfully implemented as real-time plugins for the OpenHRP simulator of the HRP2. Simulations showing the efficiency of the method are presented and discussed.
The full-scale humanoid robot RH-1 has been totally developed in the University Carlos III of Madrid. In this paper we present an advanced control system for this robot so that it can perform tasks in cooperation with humans. The collaborative tasks are carried out in a semi-autonomous way and are intended to be put into operation in real working environments where humans and robots should share the same space. Before presenting the control strategy, the kinematic model and a simplified dynamic model of the robot are presented. All the models and algorithms are verified by several simulations and experimental results.
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