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In this paper, the problem of mapping and planning in an uncertain environment is studied. A hybrid Bayesian/ frequentist formulation of the simultaneous planning, localization and mapping (SPLAM) problem is presented wherein the environment is modeled as a stationary, spatially uncorrelated random process whose stationary probabilities are fixed but unknown, and have to be estimated as the autonomous...
In this paper, the problem of motion planning of an autonomous agent in an uncertain environment is considered. The state of the augmented system is defined as the ordered pair consisting of the state of the agent and the state of the environment. At the higher level of the hierarchy, the state-space of the agent is reduced to a set of "landmarks" through the use of suitably defined control...
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