Energy-oriented optimization of the task allocation for mobile robots

Production systems need to be flexible in order to handle increasingly complex operational requirements. In many cases, mobile robots are used to flexibly connect production facilities. In this case, task allocation is a challenging procedure and should be optimized to ensure that processing deadlines are met and processing times are minimized. For this purpose, it is essential to be able to accurately predict the energy and time requirement of each action that the mobile robots could execute. This paper investigates how detailed modelling of mobile robots can reduce energy requirements and optimize planning of the logistics. Two concepts for task allocation are examined and one is presented in detail due to its applicability: global optimization by use of an open source software library and local optimization by use of an auction procedure. The global optimization method is suitable for small problems of low complexity, while the auction procedure can handle scenarios that are more complex. In this case, a central entity selects the mobile robot with the lowest bid to complete the task based on a developed prediction model for time and energy requirements.