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 10.8kg (without batteries) while retaining high links strength and rigidity. Without compromising the workspace dimension, the robot presents a very low weight-to-height ratio (9.8kg/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.
| Original language | English |
|---|---|
| Article number | 1850022 |
| Journal | International Journal of Humanoid Robotics |
| Volume | 15 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Oct 1 2018 |
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Keywords
- 3d printing
- biped robot
- dynamic modeling
- Humanoid robotics
- kinematic design
- recurrent neural networks
ASJC Scopus subject areas
- Mechanical Engineering
- Artificial Intelligence
Cite this
Design and Modeling of a Lightweight and Low Power Consumption Full-Scale Biped Robot. / Folgheraiter, Michele; Aubakir, Bauyrzhan.
In: International Journal of Humanoid Robotics, Vol. 15, No. 5, 1850022, 01.10.2018.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Design and Modeling of a Lightweight and Low Power Consumption Full-Scale Biped Robot
AU - Folgheraiter, Michele
AU - Aubakir, Bauyrzhan
PY - 2018/10/1
Y1 - 2018/10/1
N2 - 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 10.8kg (without batteries) while retaining high links strength and rigidity. Without compromising the workspace dimension, the robot presents a very low weight-to-height ratio (9.8kg/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.
AB - 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 10.8kg (without batteries) while retaining high links strength and rigidity. Without compromising the workspace dimension, the robot presents a very low weight-to-height ratio (9.8kg/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.
KW - 3d printing
KW - biped robot
KW - dynamic modeling
KW - Humanoid robotics
KW - kinematic design
KW - recurrent neural networks
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UR - http://www.scopus.com/inward/citedby.url?scp=85053058705&partnerID=8YFLogxK
U2 - 10.1142/S0219843618500226
DO - 10.1142/S0219843618500226
M3 - Article
AN - SCOPUS:85053058705
VL - 15
JO - International Journal of Humanoid Robotics
JF - International Journal of Humanoid Robotics
SN - 0219-8436
IS - 5
M1 - 1850022
ER -