Rescue Missions Bots using Active SLAM and Map Feature Extraction

The main objective of our study is to implement a heterogeneous multi-robot system for mapping and exploration. We present a novel approach where the SLAM map is used to speed up the exploration process by extracting points of interest from the map and directing the eye-bot (explorer) towards them. The first robot is equipped with a laser range finder is called range bot and is responsible for building a map of an unknown environment while navigating autonomously. Then send this map to our next robot the eye bot which is equipped with a camera for live video streaming. The eye bot use this map to extracts some desired features which can help our robotic system to identify possible threats. In our case the desired features are objects scattered in the arena. Also it extracts the position of those objects to be able to build its path through our arena given the previous knowledge of the map to give us a live stream video of those objects. The first task which is performed by the range bot is done using the active SLAM approach based on EKF and a maze solver algorithm for the robot to perform the active part which is navigating autonomously. The second task which is done by using the method of connected components for the extraction of the desired objects and their positions from the map then the robot just follows the map to reach each position. The importance of this approach is to search for survivors in search and rescue missions in a time-efficient way autonomously.