Table of Content

Open AccessOpen Access


Robot Pose Estimation Based on Visual Information and Particle Swarm Optimization

Carlos Lopez-Franco1, Javier Gomez-Avila2, Nancy Arana-Daniel3, Alma Y. Alanis

Computer Science Department, CUCEI, University of Guadalajara. Blvd. Marcelino Garcia Barragan 1421, Col. Olimpica, Guadalajara, Jalisco, Mexico, C. P. 44430
Email: 1, 2, 3

* Corresponding Author: Alma Y. Alanis,

Intelligent Automation & Soft Computing 2018, 24(2), 431-442.


This paper presents a method for 3D pose estimation using visual information and a soft-computing algorithm. The algorithm uses quaternions to represent rotations, and Particle Swarm Optimization to estimate such quaternion. The rotation estimation problem is cast as a minimization problem, which finds the best quaternion for the given data using the PSO algorithm. With this technique, the algorithm always returns a valid quaternion, and therefore a valid rotation. During the estimation process, the algorithm is able to detect and reject outliers. The simulations and experimental results show the robustness of algorithm against noise and outliers.


Cite This Article

C. Lopez-Franco, . J. Gomez-Avila, . N. Arana-Daniel and . A. Y. Alanis, "Robot pose estimation based on visual information and particle swarm optimization," Intelligent Automation & Soft Computing, vol. 24, no.2, pp. 431–442, 2018.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 808


  • 618


  • 0


Related articles

Share Link

WeChat scan