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Zero Moment Point/Inverted Pendulum-Based Walking Algorithm for the NAO Robot

Motoc, Iulia, Sirlantzis, Konstantinos, Spurgeon, Sarah K., Lee, Peter (2014) Zero Moment Point/Inverted Pendulum-Based Walking Algorithm for the NAO Robot. In: Proceeding of the 2014 IEEE/AT-EQUAL Conference on Human-Machine Systems. . pp. 63-66. IEEE (doi:10.1109/EST.2014.34) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://doi.org/10.1109/EST.2014.34

Abstract

Bipedal walking may be a difficult task to execute by a bipedal robot. Different factors such as the arm movement or the constant changing of the Center of Mass may lead to an unstable gait. This may be one of the reasons the trajectory of the Center of Mass should be calculated before making the next step. This paper presents a walking algorithm based on Zero Moment Point for the NAO robot. NAO is a 58 cm tall humanoid bipedal robot produced by the French company Aldebaran Robotics. Bipedal walking can be a quite difficult task, since the Center of Mass moves from one foot to another during the walking. For the NAO robot, walking is an even more difficult task, due to its limitations. This paper uses a Zero Moment Point-based walking algorithm in order to calculate the trajectory of the Center of Mass and obtain a stable and robust walk for NAO. The algorithm was used on a simulated environment using the NAO robot.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/EST.2014.34
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Konstantinos Sirlantzis
Date Deposited: 26 Oct 2015 12:17 UTC
Last Modified: 29 May 2019 16:12 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/51229 (The current URI for this page, for reference purposes)
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