Working with SLAM using ROS and Kinect

The main aim of deploying vision sensors in our robot is to detect objects and perform robot navigation in an environment. SLAM is a technique used in mobile robots and vehicles to build up a map of an unknown environment or update a map within a known environment by tracking the current location of a robot.

Maps are used to plan the robot trajectory and to navigate through this path. Using maps, the robot will get an idea about the environment. The main two challenges in mobile robot navigation are mapping and localization.

Mapping involves generating a profile of obstacles around the robot. Through mapping, the robot will understand how the world looks. Localization is the process of estimating a pose of the robot relative to the map we build.

SLAM fetches data from different sensors and uses it to build maps. The 2D/3D vision sensor can be used as an input to SLAM. The 2D vision sensors such as laser range finders and 3D sensors such as Kinect are mainly...