Monte Carlo Node Localization Based on Improved QUARTE Optimization

Monte Carlo-based optimization of a gamma probe system for sentinel lymph node mapping

Introduction: Sentinel lymph node biopsy (SLNB) is a standard surgical technique to identify sentinel lymph node (SLN) for the staging of early breast cancer. Nowadays, two methods are used for the identification of SLN: blue dye method aiding visually and radioactive dye using gamma detector. A wide range of gamma probe systems with different design and performance are used in...

Omnivision-based KLD-Monte Carlo Localization

Mobile robots operating in real and populated environments usually execute tasks that require accurate knowledge on their position. Monte Carlo Localization (MCL) algorithms have been successfully applied for laser range finders. However, vision-based approaches present several problemswith occlusions, realtime operation, and environment modifications. In this article, an omnivision-based MCL a...

Coevolution Based Adaptive Monte Carlo Localization

Coevolution Based Adaptive Monte Carlo Localization (CEAMCL)

An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot’s pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric enviro...

Monte Carlo Localization

In this paper we investigate robot localization with the Augmented Monte Carlo Localization (aMCL) algorithm. The goal of the algorithm is to enable a robot to localize itself in an known world. The map of the environment where the robot has to localize itself must be given to the robot beforehand. In our case the map is constructed by another robot. This map is a so called occupancy grid. An o...