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Sensors 2018, 18(3), 836; doi:10.3390/s18030836

Experimental Robot Model Adjustments Based on Force–Torque Sensor Information

System Engineering and Automation Department, University Carlos III, Av de la Universidad, 30, Madrid 28911, Spain
Author to whom correspondence should be addressed.
Received: 17 January 2018 / Revised: 6 March 2018 / Accepted: 7 March 2018 / Published: 11 March 2018
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)


The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM) to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM), is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP). Thanks to the use of information from force–torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics. View Full-Text
Keywords: force–torque sensors; balance control; humanoid robot; simplified model force–torque sensors; balance control; humanoid robot; simplified model

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Martinez, S.; Garcia-Haro, J.M.; Victores, J.G.; Jardon, A.; Balaguer, C. Experimental Robot Model Adjustments Based on Force–Torque Sensor Information. Sensors 2018, 18, 836.

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