Navigating unfamiliar environments can be challenging for visually impaired individuals due to difficulties in recognizing distant landmarks or visual cues. This work focuses on a particular form of wayfinding, specifically backtracking a previously taken path, which can be useful for blind pedestrians. We propose a hands-free indoor navigation solution using a smartphone without relying on pre-existing maps or external infrastructure. Our hybrid matching method integrates machine learning to enhance positioning accuracy, addressing real-life challenges such as odometry errors or deviations from the correct path. Testing with datasets from visually impaired individuals demonstrates the potential of our approach in providing reliable backtracking assistance.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759050 | PMC |
| http://dx.doi.org/10.1109/ipin62893.2024.10786145 | DOI Listing |
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