Optimal Trajectory Planning for Robot

Abstract:

Article Preview

A gait control system is designed for walking a slope movement according to the features of biped robot, Two BP networks are introduced into train the walking trajectory of robot and the optimal trajectory is generated by the new evolutionary approach based on particle swarm optimization. Additionally, online environmental information is collected as neural network input, and necessary joint trajectory is output for the movement. Simulations with Matlab and experiments on NAO humanoid robot testify the efficiency of the method.

Info:

Periodical:

Advanced Materials Research (Volumes 255-260)

Edited by:

Jingying Zhao

Pages:

2091-2095

DOI:

10.4028/www.scientific.net/AMR.255-260.2091

Citation:

S. H. Piao et al., "Optimal Trajectory Planning for Robot", Advanced Materials Research, Vols. 255-260, pp. 2091-2095, 2011

Online since:

May 2011

Export:

Price:

$35.00

[1] M. Vukobratovic. Zero moment point, thirty five years of its lift. International Journal of Biped Robotics, 2004, (191), pp.157-173.

[2] Q. Huang. Planning walking patterns for a biped robot, IEEE Trans. Robot. Autom. 2001, 17(3).

[3] N. M. Peiman, B. Ahmad. Mathematical simulation of a seven link biped robot on various surfaces and ZMP considerations. Applied Mathematical Modelling, 2007, 31(1) , pp.18-37.

DOI: 10.1016/j.apm.2006.06.018

[4] P. João Ferreira. Manuel Crisóstomo, A. Paulo Coimbra. ZMP trajectory reference for the sagittal plane control of a biped robot based on a human CoP and gait. The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems 2009 St. Louis, USA, pp.1588-1593.

DOI: 10.1109/iros.2009.5354408

[5] T. Sugihara. Standing Stabilizability and Stepping Maneuver in Planar Bipedalism based on the Best COM-ZMP Regulator. 2009 IEEE International Conference on Robotics and Automation, Japan, 2009, p.1966-(1971).

DOI: 10.1109/robot.2009.5152284

[6] C. L. Shih. Ascending and Descending Stairs for a Biped Robot. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 29, NO. 3, MAY 1999, pp.255-268.

DOI: 10.1109/3468.759271

[7] X. Yao, Y. Liu. A new evolutionary system for evolving artificial neural networks. IEEE Trans. on Neural Networks, 1997, 8(3): 694-713.

DOI: 10.1109/72.572107

[8] K. W. Chau, Application of a PSO-based neural network in analysis of outcomes of construction claims. Automation in Construction, 2007(16) , pp.642-646.

DOI: 10.1016/j.autcon.2006.11.008

In order to see related information, you need to Login.