IMPLEMENTATION AND TESTING MONTE CARLO LOCALIZATION METHOD ON V-REP SIMULATOR
Kata Kunci:
localization, probabilistic robotics, monte carlo localization, particle filterAbstrak
For a robot in order to be able to do navigation in a closed environment requires a way to find out information from the robot's location itself, this is often referred to as localization. Among the many approaches and methods in solving localization problems, there is an approach that involves probabilistic elements in the field of robotics known as robotics probabilistic. One of the techniques for solving the localization of the robot is to use the Monte Carlo Localization (MCL) technique which is based on the particle filter technique. The MCL technique represents the robot's confidence level with a number of sample weights (particles), with posterior probability estimates derived from the Bayesian formulation of the localization problem. Considering that the easier way to implement the model and concept of robots is through existing robot simulators, one of which is the V-REP simulator. It is also necessary to implement and implement a probabilistic robotics model through a simulator, and one of the techniques implemented in this research is the MCL technique.
Unduhan
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