Event
Distributed Sensing and Hyperdimensional Computing Enable Non-Line-of-Sight Target Perception
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Placido Mursia and other authors propose a non-line-of-sight passive target perception framework: it relies solely on distributed channel measurements from communication infrastructure to perform risk-aware classification of passive entities outside a robot's field of view, and uses hyperdimensional computing to embed the measurements into a high-dimensional representation without explicit channel reconstruction. The authors report that numerical simulations based on commercial ray tracing and validation in a ROS smart factory scenario show accuracy of up to 89% under severe occlusion, while maintaining low computational complexity and improving safety and path planning. These results come from simulations and validation results reported by the authors.
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- Non-line-of-sight passive object sensing using distributed sensing and hyperdimensional computing
The paper proposes a framework that relies solely on distributed channel measurements from communication infrastructure to sense passive entities outside a robot's field of view and perform risk-aware classification. The method uses hyperdimensional computing (HDC) to embed measurements into high-dimensional representations without explicit channel reconstruction. Numerical simulations based on commercial ray tracing and validation in a ROS smart factory scenario show accuracy of up to 89% under severe occlusion while maintaining low computational complexity.
arXiv cs.RO ·