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Bibliographic Details
Main Author: Das, Sagarnil
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.01153
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Table of Contents:
  • Localization is the challenge of determining the robot's pose in a mapped environment. This is done by implementing a probabilistic algorithm to filter noisy sensor measurements and track the robot's position and orientation. This paper focuses on localizing a robot in a known mapped environment using Adaptive Monte Carlo Localization or Particle Filters method and send it to a goal state. ROS, Gazebo and RViz were used as the tools of the trade to simulate the environment and programming two robots for performing localization.