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A general deterministic sequence for sampling d-dimensional configuration spaces
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AI
DOI：10.1007/s10846-007-9170-9.png)
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Abstract
En 中文
Previous works have already demonstrated that deterministic sampling can be competitive with respect to probabilistic sampling in sampling-based path planners. Nevertheless, the definition of a general sampling sequence for any d-dimensional configuration space satisfying the requirements needed for path planning is not a trivial issue. This paper makes a proposal of a simple and yet efficient deterministic sampling sequence based on the recursive use, over a multigrid cell decomposition, of the ordering of the 2(d) descendant cells of any parent cell. This ordering is generated by the digital construction method using a d x d matrix T-d. A general expression of this matrix (i.e. for any d) is introduced and its performance analyzed in terms of the mutual distance. The paper ends with a performance evaluation of the use of the proposed deterministic sampling sequence in different well known path planners.
Keywords:
deterministic sampling
sampling-based methods
path planning
Journal
J
IF:
2.8
Papers:
3.8K
Citations:
6.9K
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