Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Particle swarm with speciation and adaptation in a dynamic environment
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
Markerless localization for blind users using computer vision and particle swarm optimization
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
| Hi-index | 0.00 |
The visual localization problem in robotics poses a dynamically changing environment due to the movement of the robot compared to a static image set serving as environmental map. We develop a particle swarm method adapted to this task and apply elements from dynamic optimization research. We show that our algorithm is able to outperform a Particle Filter, which is a standard localization approach in robotics, in a scenario of two visual outdoor datasets, being computationally more effective and delivering a better localization result.