2018
DOI: 10.1109/lcsys.2017.2785357
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Time-Optimal Collaborative Guidance Using the Generalized Hopf Formula

Abstract: Abstract-Presented is a new method for calculating the timeoptimal guidance control for a multiple vehicle pursuit-evasion system. A joint differential game of k pursuing vehicles relative to the evader is constructed, and a Hamilton-Jacobi-Isaacs (HJI) equation that describes the evolution of the value function is formulated. The value function is built such that the terminal cost is the squared distance from the boundary of the terminal surface. Additionally, all vehicles are assumed to have bounded controls… Show more

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Cited by 24 publications
(18 citation statements)
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References 24 publications
(40 reference statements)
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“…It is important to acknowledge that both of these techniques are computationally intensive and scale poorly with the dimensionality of the underlying continuous spaces, which can generally limit their applicability to complex dynamical systems. However, recent compositional approaches have dramatically increased the tractability of lightly coupled high-dimensional systems [25], [24], [7], [8], while new analytic solutions entirely overcome the "curse of dimensionality" in some relevant cases [12], [26]. The key contribution of this work is in the principled methodology for incorporating safety into learning-based systems: we thus focus our examples on problems of low dimensionality, implicitly bypassing the computational issues, and note that our method can readily be used in conjunction with these decomposition techniques to extend its application to more complex systems.…”
Section: Contributionmentioning
confidence: 99%
“…It is important to acknowledge that both of these techniques are computationally intensive and scale poorly with the dimensionality of the underlying continuous spaces, which can generally limit their applicability to complex dynamical systems. However, recent compositional approaches have dramatically increased the tractability of lightly coupled high-dimensional systems [25], [24], [7], [8], while new analytic solutions entirely overcome the "curse of dimensionality" in some relevant cases [12], [26]. The key contribution of this work is in the principled methodology for incorporating safety into learning-based systems: we thus focus our examples on problems of low dimensionality, implicitly bypassing the computational issues, and note that our method can readily be used in conjunction with these decomposition techniques to extend its application to more complex systems.…”
Section: Contributionmentioning
confidence: 99%
“…Proceeding similar to Kirchner et al (2018b), we can generalize the Hopf formula to (1) by making a change of variables…”
Section: Viscosity Solutions With the Hopf Formulamentioning
confidence: 99%
“…For clarity in the sections to follow, we use the notation H z to refer to the Hamiltonian for systems defined by (10), and H x for systems defined by (8). Additionally, with a slight abuse of notation, we denote by J ⋆ x (p, T ) the Fenchel transform of J (x, t) with respect to the variable x at time t = T .…”
Section: B General Linear Modelsmentioning
confidence: 99%