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In recent years, the use of electric Autonomous Wheeled Mobile Robots (AWMRs) has dramatically increased in transport of the production chain. Generally, AWMRs must operate for several hours on a single battery charge. Since the energy density of the battery is limited, energy efficiency becomes a key element in improving material transportation performance during the manufacturing process. However, energy consumption is influenced by the navigation stages, because the type of motion necessary for the AWMR to perform during a mission is totally defined by these stages. Therefore, this paper analyzes methods of energy efficiency that have been studied recently for AWMR navigation stages. The selected publications are classified into planning and motion control categories in order to identify research gaps. Unlike other similar studies, this work focuses on these methods with respect to their implications for the energy consumption of AWMRs. In addition, by using an industrial Self-Guided Vehicle (SGV), we illustrate the direct influence of the motion planning stage on global energy consumption by means of several simulations and experiments. The results indicate that the reaction of the SGV in response to unforeseen obstacles can affect the amount of energy consumed. Hence, energy constraints must be considered when developing the motion planning of AWMRs.
Mohammad Mohammadpour; Lotfi Zeghmi; Sousso Kelouwani; Marc-André Gaudreau; Ali Amamou; Massinissa Graba. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots. Energies 2021, 14, 3517 .
AMA StyleMohammad Mohammadpour, Lotfi Zeghmi, Sousso Kelouwani, Marc-André Gaudreau, Ali Amamou, Massinissa Graba. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots. Energies. 2021; 14 (12):3517.
Chicago/Turabian StyleMohammad Mohammadpour; Lotfi Zeghmi; Sousso Kelouwani; Marc-André Gaudreau; Ali Amamou; Massinissa Graba. 2021. "An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots." Energies 14, no. 12: 3517.
Automated industrial vehicles are taking an imposing place by transforming the industrial operations, and contributing to an efficient in-house transportation of goods. They are expected to bring a variety of benefits towards the Industry 4.0 transition. However, Self-Guided Vehicles (SGVs) are battery-powered, unmanned autonomous vehicles. While the operating durability depends on self-path design, planning energy-efficient paths become crucial. Thus, this paper has no concrete contribution but highlights the lack of energy consideration of SGV-system design in literature by presenting a review of energy-constrained global path planning. Then, an experimental investigation explores the long-term effect of battery level on navigation performance of a single vehicle. This experiment was conducted for several hours, a deviation between the global trajectory and the ground-true path executed by the SGV was observed as the battery depleted. The results show that the mean square error (MSE) increases significantly as the battery’s state-of-charge decreases below a certain value.
Massinissa Graba; Sousso Kelouwani; Lotfi Zeghmi; Ali Amamou; Kodjo Agbossou; Mohammad Mohammadpour. Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context. Sustainability 2020, 12, 8541 .
AMA StyleMassinissa Graba, Sousso Kelouwani, Lotfi Zeghmi, Ali Amamou, Kodjo Agbossou, Mohammad Mohammadpour. Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context. Sustainability. 2020; 12 (20):8541.
Chicago/Turabian StyleMassinissa Graba; Sousso Kelouwani; Lotfi Zeghmi; Ali Amamou; Kodjo Agbossou; Mohammad Mohammadpour. 2020. "Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context." Sustainability 12, no. 20: 8541.