The STL motion-planning problem is reformulated as a shortest-path problem over a graph of convex sets to generate smooth Bézier-spline trajectories satisfying logical, timing, smoothness, and velocity constraints.
Formal methods for control synthesis: An optimization perspective,
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.RO 4years
2026 4representative citing papers
Transforms lexicographic minimum-violation STL motion planning into scalar optimization using non-uniform quantization and bit-shifting for efficient MPPI solving.
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.
Ternary logic encodings of temporal behavior trees enable mixed-integer linear programming for correct-by-construction control synthesis in linear systems.
citing papers explorer
-
Signal Temporal Logic Motion Planning via Graphs of Convex Sets
The STL motion-planning problem is reformulated as a shortest-path problem over a graph of convex sets to generate smooth Bézier-spline trajectories satisfying logical, timing, smoothness, and velocity constraints.
-
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.
-
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.
-
Ternary Logic Encodings of Temporal Behavior Trees with Application to Control Synthesis
Ternary logic encodings of temporal behavior trees enable mixed-integer linear programming for correct-by-construction control synthesis in linear systems.