What is robotic localization?

What is robotic localization?

Robot localization is the process of determining where a mobile robot is located with respect to its environment. Localization is one of the most fundamental competencies required by an autonomous robot as the knowledge of the robot’s own location is an essential precursor to making decisions about future actions.

What is grid localization?

Grid localization approximates the posterior using a histogram filter over a grid. decomposition of the pose space.

What is localization in navigation?

Robot localization denotes the robot’s ability to establish its own position and orientation within the frame of reference. Robot navigation means the robot’s ability to determine its own position in its frame of reference and then to plan a path towards some goal location.

How to localize a robot in a grid?

A localization problem with an occupancy grid map: The shaded areas represent occupied cells; the white area represents the free space; the robot moves a few steps (a robot pose is shown as a circle plus an arrow); the readings from the laser range finder at the first pose (red) are depicted as red lines.

How is the problem of robot localization solved?

The localization problem then becomes one of estimating the robot position and orientation within the map using information gathered from these sensors. Robot localization techniques need to be able to deal with noisy observations and generate not only an estimate of the robot location but also a measure of the uncertainty of the location estimate.

How is the location of a robot determined?

A mobile robot equipped with sensors to monitor its own motion (e.g., wheel encoders and inertial sensors) can compute an estimate of its location relative to where it started if a mathematical model of the motion is available. This is known as odometry or dead reckoning.

How are occupancy grid maps used in robots?

Occupancy grid maps provide a discretized representation of an environment where each of the grid cells is classified into two categories: occupied or free. Consider the scenario where a sensor on the robot can determine the distance to the nearest occupied grid cell along a given direction.