Robot localization – Adaptive Monte Carlo Localization (AMCL)

We are using the AMCL algorithm for robot localization in the given map. The AMCL algorithm is a probabilistic localization technique that uses a particle filter to track the pose of a robot in a known map. It has many configuration options that will affect the performance of localization. We can refer to the AMCL documentation at http://wiki.ros.org/amcl and http://www.probabilistic-robotics.org/.

Getting ready

Although the amcl algorithm works mostly with laser scans and laser maps, it can be extended to work with other sensor data, such as stereo vision and lidar, which produce point cloud data. During startup, the amcl node initializes its particle filter according to the parameters provided in the setup configuration file. If the initial position of the robot is not set, amcl will start at the origin of the reference frame. However, we can set the initial position in RViz using the 2D Pose Estimate button, as discussed in the...