Prediction of a Ball Trajectory for the Humanoid Robots: A Friction-Based Study

Behnam Yazdankhoo, Mohammad Navid Shahsavari, Soroush Sadeghnejad, Jacky Baltes

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Recent advances in robotics have made it necessary for robots to be able to predict actions like humans. This problem is well presented in international RoboCup competition leagues, especially for humanoid robots in challenges such as Goal-Kick from Moving Ball. In this paper, we proposed double exponential smoothing (DES), autoregressive (AR) and quadratic prediction (QP) as online methods and self-perturbing recursive least squares (SPRLS) as an offline method for prediction of the ball trajectory on ground. These prediction methods are compared in two scenarios by applying LuGre friction model. We simulated our proposed methods by Simmechanics library of MATLAB’s Simulink. By comparing results using root-mean-square error and normalized root-mean-square error, we could deduce that methods that were based on predefined models such as QP performed poorly when the friction deviated from the presumed model. Whereas numerical methods such as AR could adapt themselves to variation much better, depending on the friction force variation with time. Also offline methods such as SPRLS are good replacements for online ones when pre-training is possible.

原文英語
主出版物標題RoboCup 2018
主出版物子標題Robot World Cup XXII
編輯Dirk Holz, Katie Genter, Maarouf Saad, Oskar von Stryk
發行者Springer Verlag
頁面387-398
頁數12
ISBN(列印)9783030275433
DOIs
出版狀態已發佈 - 2019
對外發佈
事件22nd RoboCup International Competition and Symposium, RoboCup 2018 - Montréal, 加拿大
持續時間: 2018 六月 182018 六月 22

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11374 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

會議

會議22nd RoboCup International Competition and Symposium, RoboCup 2018
國家/地區加拿大
城市Montréal
期間2018/06/182018/06/22

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

指紋

深入研究「Prediction of a Ball Trajectory for the Humanoid Robots: A Friction-Based Study」主題。共同形成了獨特的指紋。

引用此