Transforms lexicographic minimum-violation STL motion planning into scalar optimization using non-uniform quantization and bit-shifting for efficient MPPI solving.
Signal temporal logic neural predictive control
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A predicate-erosion framework using contraction-based probabilistic reachable tubes turns chance-constrained STL planning for stochastic nonlinear systems into deterministic trajectory optimization that achieves high-probability specification satisfaction.
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Lexicographic Minimum-Violation Motion Planning using Signal Temporal Logic
Transforms lexicographic minimum-violation STL motion planning into scalar optimization using non-uniform quantization and bit-shifting for efficient MPPI solving.
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Feedback Motion Planning for Stochastic Nonlinear Systems with Signal Temporal Logic Specifications
A predicate-erosion framework using contraction-based probabilistic reachable tubes turns chance-constrained STL planning for stochastic nonlinear systems into deterministic trajectory optimization that achieves high-probability specification satisfaction.