Computation of cause and effect relationship for acceptance of autonomous mobile robots in industries

Abstract Autonomous mobile robot (AMR) is a programmed machine capable of maneuvering through obstacle free path to reach destination thereby reducing human labor. Prerequisite for an AMR is to self-navigate through arduous and unknown waypoints in dynamic or real-time situations over a shortest path which demands software and hardware development and interaction, using abundant electronic and mechanical components. AMRs are necessary for industries working in 24-7 work schedule to alleviate user’s performance and curb wear and tear of components in industries. Several factors govern acceptance of AMR in industries based on user feedback. In this work, authors have analyzed computationally user preferences for AMR acceptance in industries, and demonstrated their cause and effect relationship using fuzzified DEMATEL and priority ranking through TOPSIS method which has not been done previously. The results provide novel and better understanding of user behavior and attitude towards AMRs. Findings, thus, provide implications for predicting user behavior and suggest directives to increase willingness of AMR usage.

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