Towards integrated OR/CP energy optimization for robot cells

Wigström, Oskar; Lennartson, Bengt

doi:10.1109/icra.2014.6907076

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Borgstrom et al [6] optimize the path of a cabled robotic system considering constraints on total energy consumption. More recently, Wigstrom and Lennartson [27] approaches the problem of minimizing the energy consumption of a system composed of multiple interacting robots, whose tasks may be coupled by timing constraints. The authors propose an algorithm to solve the resulting nonlinear programming problem and demonstrate it for two examples that use 3 DOF manipulators.…”

Section: Related Workmentioning

confidence: 99%

Relevant factors for the energy consumption of industrial robots

Garcia

Bittencourt

Villani

2018

J Braz. Soc. Mech. Sci. Eng.

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This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry.

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Section: Related Workmentioning

confidence: 99%

Relevant factors for the energy consumption of industrial robots

Garcia

Bittencourt

Villani

2018

J Braz. Soc. Mech. Sci. Eng.

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“…For example, Sieber et al [44] formulate an LQR-like optimal control problem designed to move a formation of mobile robots to a goal while minimizing input energy and incorporating a provision for formation rigidity into the cost functional. Similarly, Wigstrom and Lennartson [45] generated trajectories that reduce energy consumption using pseudo-spectral optimal control, though paths are considered free. Coverage algorithms such as [40,46] also implement energy conservation constraints while maximizing the reach of mobile robot networks and sensing.…”

Section: Introductionmentioning

confidence: 99%

Time-Energy Optimal Cluster Space Motion Planning for Mobile Robot Formations

Stanhouse¹,

Kitts²,

Mas³

2016

Recent Advances in Robotic Systems

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The motions of a formation of mobile robots along predetermined paths are optimized according to a tunable time-energy cost function using the cluster space approach to multiagent system specification and control. Upon path-parameterizing cluster state variables describing the geometry and pose of a multirobot group, an optimal control problem is formulated that incorporates formation dynamics and state constraints. The optimal trajectory is derived numerically via a gradient search, iterating over the initial value of one costate. A multirobot formation control simulation is then used to demonstrate the effectiveness of the technique. Results indicate that a substantial tradeoff is made between energy expenditure and motion time when considered as minimization criteria in varying proportions, allowing the operator to tailor mission trajectories according to desired levels of each.

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“…The key idea is to utilize CP in order to reduce the number of nodes, and in doing so, the number of NLP sub-problems. It was suggested in Wigström and Lennartson (2014) that the algorithm may be extended to include continuous dynamics. In optimal control problems, collocation is a common approach used to approximate continuous dynamics Benson (2005).…”

Section: Introductionmentioning

confidence: 99%

An Integrated CP/OR Method for Optimal Control of Modular Hybrid Systems

Wigström

Lennartson

2014

IFAC Proceedings Volumes

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This paper concerns the optimal control of modular hybrid systems synchronized by shared variables. Instead of synchronizing the discrete dynamics of the system into one global mode before optimization, Constraint Programming (CP) is used to model the discrete dynamics of each modular system separately. Integrated in the CP solver are also classic Operations Research (OR) models in the form of Nonlinear Programs (NLPs) approximating the continuous dynamics of the system. Using CP considerably decreases the number of NLPs which must be solved, compared to that of using a traditional mixed integer nonlinear programming approach.

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Towards integrated OR/CP energy optimization for robot cells

Cited by 4 publications

References 19 publications

Relevant factors for the energy consumption of industrial robots

Relevant factors for the energy consumption of industrial robots

Time-Energy Optimal Cluster Space Motion Planning for Mobile Robot Formations

An Integrated CP/OR Method for Optimal Control of Modular Hybrid Systems

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