TY - GEN
T1 - Computational Efficient Balance Control for a Lightweight Biped Robot with Sensor Based ZMP Estimation
AU - Folgheraiter, Michele
AU - Yessaly, Alikhan
AU - Kaliyev, Galym
AU - Yskak, Asset
AU - Yessirkepov, Sharafatdin
AU - Oleinikov, Artemiy
AU - Gini, Giuseppina
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the Ministry of Education and Science of the Republic of Kazakhstan under the grant and target funding scheme agreement #328/239-2017 and by Nazarbayev University under the Faculty Development Competitive Research Grants Program award #090118FD5343.
Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/23
Y1 - 2019/1/23
N2 - This paper presents a computational efficient balance control algorithm developed for a lightweight biped. A LIP model of the robot is combined with the ZMP calculation to derive a joint space control action based on a PD controller. Furthermore, a method is implemented to estimate the ZMP directly from the center of pressure measured using the force sensors installed under the feet of the robot. This, allows a real time implementation of the controller without using the robot direct kinematics, reducing model inaccuracies and improving the controller reactivity. Simulation results and tests on the real robot prototype shows that the control system is able to compensate for external disturbances forces up to 10N reducing the oscillations of 60%.
AB - This paper presents a computational efficient balance control algorithm developed for a lightweight biped. A LIP model of the robot is combined with the ZMP calculation to derive a joint space control action based on a PD controller. Furthermore, a method is implemented to estimate the ZMP directly from the center of pressure measured using the force sensors installed under the feet of the robot. This, allows a real time implementation of the controller without using the robot direct kinematics, reducing model inaccuracies and improving the controller reactivity. Simulation results and tests on the real robot prototype shows that the control system is able to compensate for external disturbances forces up to 10N reducing the oscillations of 60%.
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U2 - 10.1109/HUMANOIDS.2018.8625016
DO - 10.1109/HUMANOIDS.2018.8625016
M3 - Conference contribution
AN - SCOPUS:85062285378
T3 - IEEE-RAS International Conference on Humanoid Robots
SP - 232
EP - 237
BT - 2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018
PB - IEEE Computer Society
T2 - 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018
Y2 - 6 November 2018 through 9 November 2018
ER -