Receding Horizon Temporal Logic Planning

By Tichakorn Wongpiromsarn, Ufuk Topcu, Richard M. Murray. IEEE Transactions on Automatic Control, 2012

310 citations recorded by the source corpus.

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Environment-Independent Task Specifications via GLTL (2017, background): “The results include open-loop and reactive control of deterministic, stochastic or non-deterministic finite-state models as well as continuous state models through appropriate finite-state abstractions (Wongpiromsarn et al., 2012; Kress-Gazit et al., 2009; Liu et al., 2013; Wolff et al., 2012; Ding ”
Safe Reinforcement Learning via Shielding (2017, background): “Wongpiromsarn et al. [24] deﬁne a receding horizon control approach that combines continuous control with discrete correctness guarantees.”
Online Verification of Automated Road Vehicles Using Reachability Analysis (2014, background): “Unfortunately, this is rarely the case due to uncertain parameters (loading of the vehicle, tire-road friction, etc.) and disturbances (road imperfections, wind, slope, etc.) so that the stability analysis of the undisturbed model becomes inconclusive.”
Survey on Scenario-Based Safety Assessment of Automated Vehicles (2020, methodology): “[166] also use Linear Temporal Logic specifications for the automatic synthesis of a trajectory planner and continuous controller.”
Model predictive control with signal temporal logic specifications (2014, background): “Receding horizon control for temporal logic has been considered before in the context of Linear Temporal Logic (LTL) [28], where the authors propose a reactive synthesis scheme for specifications with GR(1) goals.”