# SLAM for Visually Impaired People: a Survey

arXiv: https://arxiv.org/abs/2212.04745 · HTML: https://mlsanity.com/paper/2212.04745/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 178 references that are in the map.
- First posted on arXiv 9 Dec 2022.

## Builds on (most cited first, 16 of 16)

- [Show, Attend and Tell: Neural Image Caption Generation with Visual Attention](https://mlsanity.com/paper/1502.03044/) (2015)
- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age](https://mlsanity.com/paper/1606.05830/) (2016)
- [Learning Deconvolution Network for Semantic Segmentation](https://mlsanity.com/paper/1505.04366/) (2015)
- [Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge](https://mlsanity.com/paper/1609.06647/) (2016)
- [OpenVSLAM: A Versatile Visual SLAM Framework](https://mlsanity.com/paper/1910.01122/) (2019)
- [TLIO: Tight Learned Inertial Odometry](https://mlsanity.com/paper/2007.01867/) (2020)
- [DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features](https://mlsanity.com/paper/2008.05416/) (2020)
- [Egocentric Human Trajectory Forecasting with a Wearable Camera and Multi-Modal Fusion](https://mlsanity.com/paper/2111.00993/) (2021)
- [Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People](https://mlsanity.com/paper/1904.13037/) (2019)
- [Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision](https://mlsanity.com/paper/2208.08477/) (2022)
- [Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments](https://mlsanity.com/paper/1910.13249/) (2019)
- [Indoor Navigation Assistance for Visually Impaired People via Dynamic SLAM and Panoptic Segmentation with an RGB-D Sensor](https://mlsanity.com/paper/2204.01154/) (2022)
- [Virtual-Blind-Road Following Based Wearable Navigation Device for Blind People](https://mlsanity.com/paper/1904.13028/) (2019)
- [UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low vision](https://mlsanity.com/paper/2209.11336/) (2022)

## Built on by (most cited first, 1 of 1)

- [Deep Learning-Powered Visual SLAM Aimed at Assisting Visually Impaired Navigation](https://mlsanity.com/paper/2510.20549/) (2025)

## Abstract (arXiv)

In recent decades, several assistive technologies have been developed to improve the ability of blind and visually impaired (BVI) individuals to navigate independently and safely. At the same time, simultaneous localization and mapping (SLAM) techniques have become sufficiently robust and efficient to be adopted in developing these assistive technologies. We present the first systematic literature review of 54 recent studies on SLAM-based solutions for blind and visually impaired people, focusing on literature published from 2017 onward. This review explores various localization and mapping techniques employed in this context. We systematically identified and categorized diverse SLAM approaches and analyzed their localization and mapping techniques, sensor types, computing resources, and machine-learning methods. We discuss the advantages and limitations of these techniques for blind and visually impaired navigation. Moreover, we examine the major challenges described across studies, including practical challenges and considerations that affect usability and adoption. Our analysis also evaluates the effectiveness of these SLAM-based solutions in real-world scenarios and user satisfaction, providing insights into their practical impact on BVI mobility. The insights derived from this review identify critical gaps and opportunities for future research activities, particularly in addressing the challenges presented by dynamic and complex environments. We explain how SLAM technology offers the potential to improve the ability of visually impaired individuals to navigate effectively. Finally, we present future opportunities and challenges in this domain.