Open Access

ARTICLE

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 carlos.lopez@cucei.udg.mx, 2 jegomezavila@gmail.com, 3 nancy.arana@cucei.udg.mx

* Corresponding Author: Alma Y. Alanis,

Intelligent Automation & Soft Computing 2018, 24(2), 431-442. https://doi.org/10.31209/2018.100000000

Abstract

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.

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Keywords

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