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Belief space planning is concerned with the problem of finding the control policy under process and measurement uncertainties. Formulated as a stochastic control problem, the solution of a general Decentralized Partially Observed Markov Decision Process (Dec-POMDP) is a collection of feedback policies for individual agents, maximizing a joint value function. In this paper, we design (m) number of...
Planning under motion and observation uncertainties requires the solution of a stochastic control problem in the space of feedback policies. In this paper, by restricting the policy class to the linear feedback polices, we reduce the general (n2 + n)-dimensional belief space planning problem to an (n)-dimensional problem. As opposed to the previous literature that search in the space of open-loop...
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