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May 6, 2026Internet Technology Letters0 citations

An IoT ‐Based Framework for Spatial Perception and Resilient Collaborative Control in Open‐Space Human‐Machine Interaction Under Industry 5.0

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YRYao Ruan

Key Points

  • To establish a resilient collaborative control framework for safe human-machine interaction in IoT settings.
  • Developed Resilient Collaborative Control Framework (RCCF) that integrates network quality metrics with physical control strategies.
  • Utilized adaptive Extended Kalman Filter for multi-sensor data fusion under network degradation conditions.
  • Implemented a dynamic impedance controller that adjusts robotic parameters based on packet loss.
  • Achieved a collision avoidance rate of 98.5% under simulated 15% packet loss.
  • Demonstrated an end-to-end latency of 31.8 ± 2.5 ms.
  • Recorded a tracking root mean square error of 12.4 ± 1.2 mm, showing significant improvement over static controllers.

Abstract

ABSTRACT The transition toward Industry 5.0 necessitates safe human‐machine interaction (HMI) in unstructured open spaces, where Internet of Things (IoT) infrastructures serve as the primary backbone for real‐time spatial perception. However, current HMI systems frequently decouple network‐layer operations from physical‐layer control, rendering robotic actuation highly vulnerable to IoT network degradation, including communication latency and stochastic packet loss. This paper proposes a Resilient Collaborative Control Framework (RCCF) that tightly couples network quality‐of‐service (QoS) metrics with physical actuation strategies. The methodology integrates an edge‐deployed adaptive Extended Kalman Filter (EKF) for multi‐sensor fusion under compromised IoT channels, alongside a network‐aware dynamic impedance controller that modulates robotic stiffness and damping in real time based on measured packet drop rates. Experimental evaluations on the publicly available SiT (Spatial Interaction Trajectories) dataset demonstrate that, under a simulated 15% packet loss scenario, the proposed RCCF achieves a tracking root mean square error (RMSE) of 12.4 ± 1.2 mm, an end‐to‐end latency of 31.8 ± 2.5 ms, and a collision avoidance rate of 98.5% ± 0.8%, yielding statistically significant improvements over static baseline controllers (one‐way ANOVA, p < 0.05). The framework effectively mitigates physical safety risks induced by communication degradation, providing a robust cyber‐physical control architecture for dynamic HMI in complex IoT environments.

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Cite This Study

Yao Ruan (2026) studied this question.

synapsesocial.com/papers/69faa1eb04f884e66b532a0bhttps://doi.org/10.1002/itl2.70288
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