FoReCo: A Forecast-Based Recovery Mechanism for Real-Time Remote Control of Robotic Manipulators

Wireless communications represent a game changer for future manufacturing plants, enabling flexible production chains, as machinery and other components not to be restricted location by the rigid wired connections on factory floor. However, presence of electromagnetic interference in wireless spectrum may result packet loss delay, making it challenging environment meet extreme reliability requirements industrial applications. In such conditions, achieving real-time remote control, either from Edge or Cloud, becomes complex. this paper, we investigate forecast-based recovery mechanism control robotic manipulators (FoReCo) that uses Machine Learning (ML) infer lost commands caused channel. FoReCo is evaluated through both simulation experimentation prone IEEE 802.11 links, using commercial research robot performs pick-and-place tasks. Results show upon reduces trajectory error more than 34.35% simulation, experimentation. We also sufficiently lightweight deployed existing hardware.