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Autonomous vehicles energy based operation capacity planning

Szpytko Janusz, Hyla Pawel, Duarte Yorlandys Salgado

Journal of Machine Engineering

2020

Vol. 20, No. 4

126--138

The paper presents an optimization model for an Automatic Guided Vehicle (AGV) operation capacity planning with focused to complete predicted mission. To successfully complete the mission the available resources related to the mission task we need to predict set of the device operation capacity indicator: technical status of the device structure and functions, device control strategy, access to the energetic resources type and others. Paper is focusing on device control strategy of the AGV under operation optimisation results minimizing possible gaps corresponded with the access to the energy. The scenarios are proposed by a Particle Swarm Optimization (PSO) algorithm, and the AGV operation is evaluated with the State of Charge (SoC) variable. The selected SoC variable allows us to describe the simulated operation in detail over time. The model output is the optimal trajectory for the AGV system considering the working environment and the satisfaction of the mission preestablished by the user. The inputs parameters of the optimization model are validated by a real environment created in a laboratory scale. The localization system, trajectories planning, workspace mapping and AGV control system concepts are briefly described, as well as the artificial intelligence used as methods and tools for AGV working control, to guide the discussion towards the contribution proposed.