FastSLAM with Look-ahead RBPF
نویسندگان
چکیده
In this paper we present an implementation of the Rao-Blackwellised particle filtering (RBPF) with one step look-ahead and apply the algorithm within the domain of agent navigation. Specifically we tackle the simultaneous localization and mapping problem (SLAM), which describes how a agent must concurrently attempt to determine its location and generate a map of the surrounding landmarks. Our implementation is built on top of previous implementation of normal RBPF using a technique called fastSLAM. We compare the performance of normal RBPF and look-ahead RBPF in terms of computational time and accuracy of state estimation.
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