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Map Building And Robot Exploration
Generating maps is one of the fundamental tasks of mobile robots. Many successful robotic systems use maps of the environment to perform their tasks. The questions of how to represent environments and how to acquire models using this representation therefore is an active research area. Exploration is the task of guiding a vehicle during mapping such that it covers the environment with its sensors. In addition to the mapping task, efficient exploration strategies are also relevant for surface inspection, mine sweeping, or surveillance.
To generate the map of the environment of the robot we used coverage maps as a new probabilistic way to represent the belief of the robot about the state of the environment. In contrast to occupancy grids in which each cell is considered as either occupied or free, coverage maps represent in each cell of a given discretization a posterior about the amount this cell is covered by an object. Since the robot usually does not know the true coverage of a grid cell it maintains a probabilistic belief p(cl) about the coverage of the cell cl. To update a coverage map based whenever sensor data arrives, we apply a Bayesian update scheme similar to that of occupancy grids.
Exploration is defined as the act of moving through an unknown environment while building a map that can be used for subsequent navigation. A good exploration strategy is one that generates a complete or nearly complete map in a reasonable amount of time. One of the approaches to exploration is based on the detection of frontiers, regions on the border between space known to be open and unexplored space. The central idea behind frontier-based exploration is: To gain the most new information about the world, move to the boundary between open space and uncharted territory. Frontiers are regions on the boundary between open space and unexplored space. When a robot moves to a frontier, it can see into unexplored space and add the new information to its map. As a result, the mapped territory expands, pushing back the boundary between the known and the unknown. By moving to successive frontiers, the robot can constantly increase its knowledge of the world. This strategy is called frontier-based exploration.
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