Task allocation and trajectory planning for multiple agents in the presence of obstacle and connectivity constraints with mixed-integer linear programming

Autor(es)

Afonso, Rubens J. M. ^{[1, 2]} ; Maximo, Marcos R. O. A. ^[3] ; Galvao, Roberto K. H. ^[2]

Afiliação do(s) autor(es)

^[1] Tech Univ Munich, Inst Flight Syst Dynam, Dept Aerosp & Geodesy, Bavaria - Germany

^[2] Inst Tecnol Aeronaut, Elect Engn Div, Sao Paulo - Brazil

^[3] Inst Tecnol Aeronaut, Autonomous Computat Syst Lab LAB SCA, Div Comp Sci, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL; v. 30, n. 14 JUL 2020.
• Citações Web of Science: 0

Resumo

This article addresses the problem of maneuvering multiple agents that must visit a number of target sets, while enforcing connectivity constraints and avoiding obstacle as well as interagent collisions. The tool to cope with the problem is a formulation of model predictive control including binary decision variables. In this regard, two mixed-integer linear programming formulations are presented, considering a trade-off between optimality and scalability between them. Simulation results are also shown to illustrate the main features of the proposed approaches. (AU)

• Processo FAPESP: 16/03647-3 - Desenvolvimento e Implementação de Algoritmos de Caminhada para Robôs Humanoides
• Beneficiário: Rubens Junqueira Magalhães Afonso
• Modalidade de apoio: Auxílio à Pesquisa - Regular