Simultaneous localization and mapping (SLAM) is a problem that has been explored for the past few decades. SLAM deals with the concept of a robot being introduced into an environment in which it has no prior knowledge. Then, through the use of sensors, the robot is able to map its environment while simultaneously determining its position within the given area. While there has been extensive research into the development of methods by which this problem can be solved, not much has been done on what to do with the resulting maps once they are produced. The research conducted deals with maps that are generated of indoor environments where some object such as tables and chairs can possibly change location within their environment, making storing their location unnecessary. There were several methods explored regarding the ability to remove such objects from the environment without unintentionally removing objects that are needed to be kept. The methods and their implementations are then integrated within the Robotics Operating System (ROS)
