@Article{2018.100000000,
AUTHOR = {Carlos Lopez-Franco, Javier Gomez-Avila, Nancy Arana-Daniel, Alma Y. Alanis},
TITLE = {Robot Pose Estimation Based on Visual Information and Particle Swarm Optimization},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {2},
PAGES = {431--442},
URL = {http://www.techscience.com/iasc/v24n2/39769},
ISSN = {2326-005X},
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.},
DOI = {10.31209/2018.100000000}
}