Abstract
This paper introduces the design methodology, the modeling and the power consumption tests for a newly developed biped robot equipped with 12 DOFs. The robot is 1.1 meters tall (lower limbs) which makes it comparable in dimension with other state-of-the-art full-scale humanoids. By using a combination of 3D printing techniques and lightweight materials, the system weighs only 10.8[Formula: see text]kg (without batteries) while retaining high links strength and rigidity. Without compromising the workspace dimension, the robot presents a very low weight-to-height ratio (9.8[Formula: see text]kg/m) that translates into a safer operation and reduced energy consumption. To perform elementary locomotion primitives, e.g., changing the support from one foot to the other or lifting its body, the robot prototype consumes only 65 watts. Simulation results demonstrate the suitability of the robot’s kinematics to perform walking motion and predict an average power consumption of 200 watts. The direct kinematics of the robot is presented together with its inverse dynamics based on a Chaotic Recurrent Neural Network (CRNN). The adaptive model is identified using a recursive least squares algorithm that allows the CRNN to predict the torques at different step lengths with a MSE of 0.0057 on normalized data.