DynoJEPP introduces directed factors in factor graphs to jointly optimize estimation, prediction, and planning while preventing feedback corruption that causes unsafe behavior in dynamic environments.
borglab/gtsam
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Derives first-principles noise models for FMCW radar and proposes a factor graph estimator that shows superior robustness and accuracy for inertial navigation in simulations and field experiments.
citing papers explorer
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DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments
DynoJEPP introduces directed factors in factor graphs to jointly optimize estimation, prediction, and planning while preventing feedback corruption that causes unsafe behavior in dynamic environments.
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On the Characterization and Limits of 4D Radar for Aided Inertial Navigation
Derives first-principles noise models for FMCW radar and proposes a factor graph estimator that shows superior robustness and accuracy for inertial navigation in simulations and field experiments.