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.