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Title:Energy-efficient routing of a multi-robot station: A flexible time-space network approach
Authors:J. Xin, C. Meng, A. D’Ariano, F. Schulte, J. Peng, R.R. Negenborn

Journal:IEEE Transactions on Automation Science and Engineering

Abstract:This paper investigates a novel routing problem of a multi-robot station in a manufacturing cell. In the existing literature, the objective is to minimize the cycle time or energy consumption separately. The routing problem considered in this paper aims to reduce the cycle time and energy consumption jointly for each robot while avoiding collisions between these robots. For this routing problem, we propose a new flexible time-space network model that allows us to reduce energy consumption while minimizing the cycle time. The corresponding optimization problem is Mixed-Integer Nonlinear Programming (MINLP). For addressing its computational complexity, this paper designs a metaheuristic algorithm tailored to the studied problem and proposes an e-constraint algorithm to study the trade-off between these two objectives. We conduct industrially relevant simulation experiments of case studies to show its effectiveness, in comparison to a conventional method, two state-of-the-art solvers, and two commonly-used metaheuristics. The results show that the proposed methodology can reduce energy consumption by up to 30% without compromising the cycle time. Meanwhile, the proposed algorithm can provide efficient solutions within a reasonable computation time.

Reference:Energy-efficient routing of a multi-robot station: A flexible time-space network approach. J. Xin, C. Meng, A. D’Ariano, F. Schulte, J. Peng, R.R. Negenborn. Accepted for publication in IEEE Transactions on Automation Science and Engineering, 2022.
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