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

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Author(s):	Afonso, Rubens J. M. ^{[1, 2]} ; Maximo, Marcos R. O. A. ^[3] ; Galvao, Roberto K. H. ^[2] Total Authors: 3
Affiliation:	^[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 Total Affiliations: 3
Document type:	Journal article
Source:	INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL; v. 30, n. 14 JUL 2020.
Web of Science Citations:	0
Abstract
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)

FAPESP's process:	16/03647-3 - Development and Implementation of Walking Algorithms for Humanoid Robots
Grantee:	Rubens Junqueira Magalhães Afonso
Support Opportunities:	Regular Research Grants