@inbook{8efa721a19ef4a2fa859b4ca8acd8457,
title = "Application of RBFNN for Humanoid robot real time optimal trajectory generation in running",
abstract = "In this paper, a method for trajectory generation in running is proposed with Radial Basis Function Neural Network, which can generate a series of joint trajectories to adjust humanoid robot step length and step time based on the sensor information. Compared with GA, RBFNN use less time to generate new trajectory to deal with sudden obstacles after thorough training. The performance of the proposed method is validated by simulation of a 28 DOF humanoid robot model with ADAMS.",
author = "Xusheng Lei and Jianbo Su",
year = "2004",
doi = "10.1007/978-3-540-28648-6\_1",
language = "英语",
isbn = "3540228438",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1--6",
editor = "Fuliang Yin and Chengan Guo and Jun Wang",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "德国",
}