Abstract
Freespace navigation for autonomous robots is of growing industrial impact, especially in the logistics and warehousing domain. In this work, we describe a multiagent simulation solution to the physical vehicle routing problem, which extends the physical traveling salesman problem —a recent benchmark used in robot motion planning research— by considering more than one concurrent vehicle.
For the interaction of vehicles, we compute the collision of physical bodies and then apply the impact resulting from the elastic collision. A multi-threaded controller is implemented which forwards the proposed actions from each individual robot’s controller to the environment real-time simulator. For computing an optimized assignment of the pickup and delivery tasks to the vehicles we apply nested Monte-Carlo tree search.
In the experiments, we study the problem of robot navigation for automated pickup and delivery of shelves to and from picking stations.
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Previously KIVA Systems.
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A video animation of the solution process is avaialble at https://bitbucket.org/Denis_Golubev/pvrp/src.
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Edelkamp, S., Golubev, D., Greulich, C. (2016). Solving the Physical Vehicle Routing Problem for Improved Multi-robot Freespace Navigation. In: Friedrich, G., Helmert, M., Wotawa, F. (eds) KI 2016: Advances in Artificial Intelligence. KI 2016. Lecture Notes in Computer Science(), vol 9904. Springer, Cham. https://doi.org/10.1007/978-3-319-46073-4_14
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DOI: https://doi.org/10.1007/978-3-319-46073-4_14
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