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|Title: ||Visual based SLAM using modified PSO|
|Authors: ||William, Low|
Nagarajan, Ramachandran, Prof. Dr.
Sazali, Yaacob, Prof. Dr.
|Keywords: ||Autonomous robot;Map building;Localization;Simultaneous Localization and Mapping (SLAM);Particle Swarm Optimization (PSO)|
|Issue Date: ||21-May-2010|
|Publisher: ||Institute of Electrical and Electronics Engineers (IEEE)|
|Series/Report no.: ||Proceedings of the 6th International Colloquium on Signal Processing and Its Applications (CSPA) 2010|
|Abstract: ||Simultaneous Localization and Mapping (SLAM) addresses the problem of a robot
navigating and acquiring spatial models of initially unknown environments, without an
absolute localization means. To solve this problem, we propose a mapping system that
builds feature-based geometrical maps by applying a modified Particle Swarm
Optimization (PSO) algorithm. Particles are defined as the location of individual features
in the environment where the size of the swarm increases as the features are reobserved
at different positions. PSO adjusts the velocity and location of particles
towards a target (feature location) as the particles move around the constrained 2-
dimensional search space. Finally, the particles will converge around an optimum
feature location. The mobile robot is also localized with respect to this map
simultaneously. It is demonstrated that accurate feature locations can be obtained using
the proposed technique.|
|Description: ||Link to publisher’s homepage at http://ieeexplore.ieee.org/|
|Appears in Collections:||Conference Papers|
Sazali Yaacob, Prof. Dr.
Ramachandran, Nagarajan, Prof. Dr.
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