ROSYJan 30, 2018

On the Use of the Observability Gramian for Partially Observed Robotic Path Planning Problems

arXiv:1801.09877v117 citations
Originality Synthesis-oriented
AI Analysis

This addresses a potential pitfall for researchers and practitioners in robotics and control systems, but it is incremental as it critiques an existing method rather than introducing a new one.

The paper tackled the problem of using the observability Gramian as a surrogate for estimation performance in robotic path planning under observation uncertainty, finding that this approach can lead to irrelevant or misleading trajectories.

Optimizing measures of the observability Gramian as a surrogate for the estimation performance may provide irrelevant or misleading trajectories for planning under observation uncertainty.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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