Rapid determination of optimal laser range finder placement is becoming of increased importance in both computer vision and robotics. The need of next-best-view algorithms for intelligent decisions in where to place the laser range finder is important for scanning both objects and landscapes to assure that the scene is fully realized and can be registered accurately. Presented here are methods for determining sensor placement to maximize the amount of information that is learned about a scene or object. Using occupancy grids of voxels and ray tracing, the placement of the sensor can be optimized for maximum collection of new data. This work provides fast algorithms that determine optimal sensor placement both outside an object of interest and inside of a closed environment. These methods take into consideration the limitations of the sensor, the interaction of the sensor to the environment, and its placement in only known areas to restrict the search space.
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