This research models signal behavior in indoor environments with humanoid robots, suggesting improved communication frameworks.
The increasing deployment of humanoid robots in indoor environments such as smart factories, laboratories, offices, and hospitals poses new challenges to millimeter-wave wireless communication systems. Existing human body obstruction models, while effective at characterizing pedestrian-induced signal attenuation, are not designed to directly capture the structural geometry, material composition, and controlled mobility of humanoid robotic platforms. In this work, we first reproduce a well-established human-body-based propagation model under comparable indoor conditions and subsequently extend this hybrid framework to controlled humanoid-based scenarios by combining double knife-edge diffraction (DKED) with a modified street-canyon reflection model operating at 28 GHz. Compared to existing human-based studies, the proposed approach explicitly incorporates the material properties of the humanoid robot’s envelope through a calibrated correction factor and accounts for its controlled lateral movements. An indoor measurement campaign using three programmable humanoid robots was conducted to evaluate the model. Experimental results show that humanoid robots can reproduce attenuation trends and obstruction dynamics consistent with those reported in prior human-body blockage studies, while offering improved repeatability and greater experimental control. The proposed framework provides a practical and reproducible tool for modeling indoor millimeter-wave channels under controlled humanoid-based experimental conditions, in environments involving mobile robotic agents.
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Nseme et al. (2026) studied this question.
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