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Real-Time Stochastic Optimal Control for Multi-agent Quadrotor Systems
[article]
2020
arXiv
pre-print
This paper presents a novel method for controlling teams of unmanned aerial vehicles using Stochastic Optimal Control (SOC) theory. The approach consists of a centralized high-level planner that computes optimal state trajectories as velocity sequences, and a platform-specific low-level controller which ensures that these velocity sequences are met. The planning task is expressed as a centralized path-integral control problem, for which optimal control computation corresponds to a probabilistic
arXiv:1502.04548v6
fatcat:l4sneapdy5enfegjkeakxs4yae