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- W4210430624 abstract "As in all distributed systems, having an accurate access to a global notion of time is vital for a modular robot's modules to coordinate their activities and accomplish their goal. In this paper, we present and compare two methods for clock skew compensation to enhance the performance of network-wide time synchronization in modular robots with neighbor-to-neighbor communication. The first one, Adaptive Rate Search (ARS), uses a light weight adaptive search method to adapt the drift rate of local clocks. The second one, combines Linear Regression with Bayes estimation (LR+) to reduce the accumu-lative error induced during the propagation of synchronization messages on large number of hops. We evaluate both methods with Blinky Block robots: using a real modular robots system and simulation. The results show that both methods LR+ and ARS present a significant error reduction compared to least-square linear regression used in previous state of the art synchronization protocol for modular robots with neighbor-to-neighbor communication." @default.
- W4210430624 created "2022-02-08" @default.
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- W4210430624 date "2021-11-23" @default.
- W4210430624 modified "2023-10-18" @default.
- W4210430624 title "Enhanced Precision Time Synchronization for Modular Robots" @default.
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- W4210430624 doi "https://doi.org/10.1109/nca53618.2021.9685103" @default.
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