Stochastic-Geometry-aided Performance Analysis in AMR-to-AMR Communications under Task-Induced Obstructed LoS Blockages

This paper analyzes partial blockages from onboard luggage or from human riders on the AMR, defined as taskinduced Obstructed LoS (OLoS) blockages, for autonomous mobile robot (AMR)-to-AMR communications, called R2R communications, by a stochastic-geometry-aided analytical framework. Our framework treats task-induced OLoS blockages associated with AMRs as a marked Poisson point process with blockage angular widths for their antennas. This key idea enables our framework to reflect the interference from multiple AMRs with blockage effects, including OLoS and non-line-of-sight (NLoS) cases, in the performance analysis. Our analytical results showed that task-induced OLoS blockages contributed to reducing the interference for an targeting AMR, especially in a regime where blockages from buildings were weak. As a result, the packet reception ratio increased at using the best angular width by 9% below using the worst angular width.