Energy-Optimal Timing of Robot Stations Subject to Gaussian Disturbances

Paper in proceeding, 2019

This paper proposes an optimization model for optimizing the energy use of industrial robots in production systems affected by stochastic disturbances. In the model there are a number of operations that needs to be completed by the robots before a deadline. The operations are of two types, one type that can not be controlled and have stochastic execution times. The other type are robot movements, and by extending their execution times energy can be saved. The goal of the optimization is to find the optimal combination of execution times for the robot movements, while meeting the deadline with a given probability.