Relocalization is a critical concept in robotics, specifically in the context of autonomous navigation and Simultaneous Localization and Mapping (SLAM). It refers to the ability of a robot to determine its current location in a map that it previously built or in a known environment, particularly after it has lost track of its position due to an error, disturbance, or after it has been manually moved (also known as the "kidnapped robot" problem).
There are many reasons why a robot might lose track of its location. Sensor noise or failure, fast movements, or environments with few distinctive features can cause a robot to lose its bearings. Even if the robot has a good map, if it doesn't know its location within that map, it can't navigate effectively.
That's where relocalization comes in. When a robot realizes it's lost, it will try to match its current sensor readings (like images from a camera or readings from a LiDAR) to the map or to previous sensor readings. If it finds a match, it can "relocalize" itself, effectively determining its current location and orientation.
For a rescue robot, relocalization is crucial. These robots often operate in challenging and unpredictable environments where there's a high chance of getting lost. If a rescue robot gets disoriented, it needs to be able to relocalize itself quickly and accurately so it can continue its mission.