##

11.6.2 Sampling-Based Approaches

Since probabilistic I-space computations over continuous spaces
involve the evaluation of complicated, possibly high-dimensional
integrals, there is strong motivation for using sampling-based
approaches. If a problem is nonlinear and/or non-Gaussian, such
approaches may provide the only practical way to compute probabilistic
I-states. Two approaches are considered here: grid-based sampling and
particle filtering. One of the most common applications of the
techniques described here is mobile robot localization, which is
covered in Section 12.2.

**Subsections**

Steven M LaValle
2020-08-14