Multitasking collision-free optimal motion planning algorithms in Euclidean spaces

Autor(es)

Ipanaque Zapata, Cesar A. ^[1] ; Gonzalez, Jesus ^[2]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Dept Matemat, Ave Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP - Brazil

^[2] Inst Politecn Nacl, Dept Matemat, Ctr Invest & Estudios Avanzados IPN Av, Numero 2508, Mexico City 07000, DF - Mexico

• Tipo de documento: Artigo Científico
• Fonte: DISCRETE MATHEMATICS ALGORITHMS AND APPLICATIONS; v. 12, n. 3 JUN 2020.
• Citações Web of Science: 0

Resumo

We present optimal motion planning algorithms which can be used in designing practical systems controlling objects moving in Euclidean space without collisions. Our algorithms are optimal in a very concrete sense, namely, they have the minimal possible number of local planners. Our algorithms are motivated by those presented by Mas-Ku and Torres-giese (as streamlined by Farber), and are developed within the more general context of the multitasking (a.k.a. higher) motion planning problem. In addition, an eventual implementation of our algorithms is expected to work more efficiently than previous ones when applied to systems with a large number of moving objects. (AU)

• Processo FAPESP: 18/23678-6 - Espaços de configurações no problema de planificação de movimento simultâneo livre de colisões
• Beneficiário: Cesar Augusto Ipanaque Zapata
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado