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**Harvard**

Vergnano, A., Thorstensson, C., Lennartson, B., Falkman, P., Pellicciari, M., Leali, F. och Biller, S. (2012) *Modeling and Optimization of Energy Consumption in Cooperative Multi-Robot Systems*.

** BibTeX **

@article{

Vergnano2012,

author={Vergnano, A. and Thorstensson, Carl and Lennartson, Bengt and Falkman, Petter and Pellicciari, M. and Leali, F. and Biller, S.},

title={Modeling and Optimization of Energy Consumption in Cooperative Multi-Robot Systems},

journal={IEEE Transactions on Automation Science and Engineering},

issn={1545-5955},

volume={9},

issue={2},

pages={423-428},

abstract={Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. Note to Practitioners-The motivation for this work is the great interest of companies on energy consumption optimization, looking for cost reduction and sustainability in manufacturing. Existing optimization methods focus on different levels of details. A high-level model would be able to optimize the overall system. Unfortunately, due to the high computational cost, it can hardly consider the deep level of mechanical and electrical parameters, which determine the real energy consumption. This paper presents a novel method to embed detailed energy consumption models into a scheduling optimization problem. An effective parameterization of the time variables reduces the model complexity, allowing the optimizer to reschedule the complete sequence of operations for minimizing the total energy consumption, while keeping a fixed cycle time. The method has been integrated into a commercial tool for robot programming. The optimization is applicable both on new and existing robotic systems, since the required modifications are limited to the operations rescheduling, and no investments on new hardware are expected.},

year={2012},

keywords={Energy optimization, mathematical programming, robot cells, scheduling and coordination; system modeling and simulation},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 160028

A1 Vergnano, A.

A1 Thorstensson, Carl

A1 Lennartson, Bengt

A1 Falkman, Petter

A1 Pellicciari, M.

A1 Leali, F.

A1 Biller, S.

T1 Modeling and Optimization of Energy Consumption in Cooperative Multi-Robot Systems

YR 2012

JF IEEE Transactions on Automation Science and Engineering

SN 1545-5955

VO 9

IS 2

SP 423

OP 428

AB Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. Note to Practitioners-The motivation for this work is the great interest of companies on energy consumption optimization, looking for cost reduction and sustainability in manufacturing. Existing optimization methods focus on different levels of details. A high-level model would be able to optimize the overall system. Unfortunately, due to the high computational cost, it can hardly consider the deep level of mechanical and electrical parameters, which determine the real energy consumption. This paper presents a novel method to embed detailed energy consumption models into a scheduling optimization problem. An effective parameterization of the time variables reduces the model complexity, allowing the optimizer to reschedule the complete sequence of operations for minimizing the total energy consumption, while keeping a fixed cycle time. The method has been integrated into a commercial tool for robot programming. The optimization is applicable both on new and existing robotic systems, since the required modifications are limited to the operations rescheduling, and no investments on new hardware are expected.

LA eng

DO 10.1109/TASE.2011.2182509

LK http://dx.doi.org/10.1109/TASE.2011.2182509

OL 30