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Erschienen in:
Comparative Analysis of Quasi-Differential Approaches in Inverse Kinematics Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

A Receding Horizon Push Recovery Strategy for Balancing the iCub Humanoid Robot

verfasst von : Stefano Dafarra, Francesco Romano, Francesco Nori

Erschienen in: Advances in Service and Industrial Robotics

Verlag: Springer International Publishing

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Abstract

Balancing and reacting to strong and unexpected pushes is a critical requirement for humanoid robots. We recently designed a capture point based approach which interfaces with a momentum-based torque controller and we implemented and validated it on the iCub humanoid robot. In this work we implement a Receding Horizon control, also known as Model Predictive Control, to add the possibility to predict the future evolution of the robot, especially the constraints switching given by the hybrid nature of the system. We prove that the proposed MPC extension makes the step-recovery controller more robust and reliable when executing the recovery strategy. Experiments in simulation show the results of the proposed approach.

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Vorheriges Kapitel Precise Positioning of a Robotic Arm Manipulator Using Stereo Computer Vision and Iterative Learning Control
Nächstes Kapitel Neural Networks for Real-Time, Probabilistic Obstacle Detection
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Metadaten
Titel
A Receding Horizon Push Recovery Strategy for Balancing the iCub Humanoid Robot
verfasst von
Stefano Dafarra
Francesco Romano
Francesco Nori
Copyright-Jahr
2018
Buch
Advances in Service and Industrial Robotics

Print ISBN: 978-3-319-61275-1

Electronic ISBN: 978-3-319-61276-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-61276-8_33

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