Data-driven acceleration of mixed-integer bilinear programs: a comparative study for robot motion planning

This paper presents a comparative study of data-driven acceleration techniques for mixed-integer bilinear programs (MIBLPs) applied to robot motion planning. MIBLPs combine discrete decision variables and nonlinear constraints, making them computationally challenging for real-time robotics applicati...

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Autor principal:	Xuan Lin
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2026-01-01
coleção:	Frontiers in Robotics and AI
Assuntos:	trajectory optimization robot motion planning optimal control mixed-integer bilinear programs mathematical programs with complementarity constraints
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/frobt.2025.1656564/full
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