Abstract
Mapping for mobile robots integrates noisy, spurious sensor data into a single coherent map useful for navigational purposes. The Bayesian framework to mapping is contrasted to the evidential framework, and a sensor model is described for range sensors to work with evidential mapping. The model is simulated and evaluated under varying parameters and in different test environments.
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