Abstract
Imagine a world in which robots are a part of everyday life, performing elegant and safe motions to accomplish complex tasks. To achieve this vision, robots will need access to extensive computational resources. Cloud-based computers have the potential to provide the needed computing power, while lowering robot cost, space, and energy requirements. Academia and industry are already exploring the cloud as a purveyor of data in a wide variety of applications, and have shown the benefit of the cloud for accelerating offline- and pre-computations.But what about interactive/online computation, as is often required by robot motion planning? This paper presents an economics-based argument that it is possible to extend a robot’s useful service life and battery-based operation time, improve its efficiency and profitability, and reduce its initial costs, by using the cloud in complex online and interactive computations. Gaining these benefits presents new, open research challenges, including: how to cost-effectively allocate cloud-based parallel computation, how to handle the unavoidable network-related bottlenecks, and how to design algorithms that distribute computation between the cloud and the robot.
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- 1.
As of March 2018, Amazon offers 1-core servers at $0.085/h, and 36-core at $3.06/h.
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Acknowledgements
We thank Jonathan Lynn for useful discussions regarding economic models. This research was supported in part by the U.S. National Science Foundation (NSF) under awards CCF-1533844 and IIS-1149965 and the U.S. National Institutes of Health (NIH) under award R01EB024864.
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Ichnowski, J., Prins, J., Alterovitz, R. (2020). The Economic Case for Cloud-Based Computation for Robot Motion Planning. In: Amato, N., Hager, G., Thomas, S., Torres-Torriti, M. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-28619-4_8
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