Mobile Robot Localization using Particle Filters and Sonar Sensors

Abstract

Nowadays, nearly all mobile robotic tasks require some knowledge of the robot location in the environment. For example, those tasks involving the robot to reach a specific target require knowledge about the current robot pose in order to plan a path to the goal. Also, exploration tasks require some estimate of the robot pose in order to decide whether a specific region has been already visited by the robot or not. The problem of computing the robot pose is known as the mobile robot localization problem. The mobile robot localization problem appears in many flavours. In some cases, only a qualitative pose estimate is needed. For example, for high level spatial reasoning, the robot may only need to know if a certain area, such as a room, has been previously visited or not. This kind of localization is commonly named weak localization. In some other cases, quantitative pose estimates with respect to a fixed reference frame are required. For example, to build metric maps, such as occupancy grids, the robot needs accurate numerical estimates of its pose in the space. This approach to localization is usually referred to as strong localization.