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Task allocation and trajectory planning for multiple agents in the presence of obstacle and connectivity constraints with mixed‐integer linear programming
Author(s) -
Afonso Rubens J.M.,
Maximo Marcos R.O.A.,
Galvão Roberto K.H.
Publication year - 2020
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5092
Subject(s) - obstacle , integer programming , scalability , mathematical optimization , linear programming , task (project management) , computer science , binary number , integer (computer science) , motion planning , model predictive control , binary decision diagram , mathematics , control (management) , algorithm , artificial intelligence , robot , engineering , arithmetic , systems engineering , database , political science , law , programming language
Summary 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.

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