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This paper introduces a walking path generation method specifically developed for the Smart Cane, which is a RNA (Robotic Navigation Assistance Device) aimed at enhancing indoor navigation for visually impaired individuals. The proposed approach combines the utilization of a LIPM (Linear Inverse Pendulum Model) and LFPC (Linear Foot Placement Controller) motion primitives to generate walking paths specifically designed for visually impaired individuals. The primary objective is to generate paths that conform to human motion constraints, thereby guaranteeing an efficient and natural navigation experience. Integrating autonomous navigation framework, the Smart Cane facilitates safe and effective guidance for visually impaired participants in the indoor environments. Furthermore, comparative experiments have been conducted to validate the effectiveness of the proposed method, providing evidence of its capability to generate walking paths that conform to human motion constraints. The experiment results indicate that the proposed walking path generation method is a promising solution to enhance the navigation experience of visually impaired individuals.

Improving Walking Path Generation through Biped Constraint in Indoor Navigation System for Visually Impaired Individuals