3 papers indexed
Chun-Wei Kong, Zachary Donovan, Morteza Lahijanian, Jay McMahon
We present CS-P2L, a framework coupling covariance steering (CS) with the Pick-to-Learn (P2L) meta-algorithm for certified controller synthesis over high-fidelity stochastic simulators. The method iteratively evaluates policies on simulator rollouts, tightens surrogate constraint…
Yusif Razzaq, Anne Theurkauf, Nisar Ahmed, Morteza Lahijanian
In this paper, we address the challenge of multi-objective motion planning for systems under kinodynamic constraints. We consider three problem classes: (i) lexicographic optimization, in which objectives are minimized according to a strict priority ordering, (ii) constrained opt…
Rayan Mazouz, Qi Heng Ho, Zachary N. Sunberg, Morteza Lahijanian
We address sampling-based motion planning for continuous-time stochastic systems under process and measurement uncertainty, with probabilistic guarantees on safety and performance. The robot dynamics are modeled as a continuous-time linear stochastic differential equation, while…