Abstract
Transportation tasks within warehouses are nowadays more and more solved using of fleets of autonomous robots. A fleet allows coordinating the different robots in such a way that it balance the load caused by transportation tasks. This allows the robot fleet to be a cost-efficient solution for moderate and changing loads compared to fixed conveyor belts.
To allow such a flexible load balancing it is necessary to estimate the time it may take to perform a certain transportation. This is of interest if different transportation tasks can be assigned to an individual robot and the order may have an impact on the time spent to perform a transportation task.
In this paper, we will present a method which can learn to estimate the time spent on certain transportation tasks. The method is evaluated per its prediction accuracy on a different set of data which were obtained from the deployment of a robotic fleet in an industrial environment.
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Acknowledgement
This work is supported by the Austrian Research Promotion Agency (FFG) under grant 843468.
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Mühlbacher, C., Gspandl, S., Reip, M., Steinbauer, G. (2018). Estimation of the Traversal Time for a Fleet of Industrial Transport Robots. In: Ferraresi, C., Quaglia, G. (eds) Advances in Service and Industrial Robotics. RAAD 2017. Mechanisms and Machine Science, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-61276-8_40
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DOI: https://doi.org/10.1007/978-3-319-61276-8_40
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