Path Recommender for Mobile Robot in Multi‐Robot System

The paper presents an intelligent approach for computing a path for mobile robot in a multi‐robot environment. Based on the personal requirement and user's feedback, the robot transits from predetermined starting position to a defined goal position. The solution is achieved through the effective blending of content‐based filtering with K‐NN path recommendation. The goal of this merging behaviour is to leverage the combined merits of recommendation and the mechanism for updating the position. Specifically, the proposed paper focus the integration of path recommendation using a filtering approach through past history to accomplish the task of object transportation from source to destinations. The discussed approach is validated through simulation using programming in a C environment. The evaluation demonstrates the ability and efficiency to achieve minimal path, time and collision freeness. Performance of the proposed approach with other existing approaches such as QCOV‐R, MCS, PRRS and DRS has been analysed to witness the efficiency.