Huang Sen, Zhao Jinjing, Zhong Yihan, Liu Yiding, Xu Shengyong
School of Electronics, Peking University, Beijing 100871, China.
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Sensors (Basel). 2025 Sep 5;25(17):5536. doi: 10.3390/s25175536.
Remote Sighted Assistance (RSA) systems provide visually impaired people (VIPs) with real-time guidance by connecting them with remote sighted agents to facilitate daily travel. However, unfamiliar environments often complicate decision-making for agents and can induce anxiety in VIPs, thereby reducing the effectiveness of the assistance provided. To address this challenge, this paper proposes a video-based map assistance method. By pre-recording pedestrian path videos and aligning them with geographic locations, the system enables route preview and enhances navigation guidance. This study introduces a factor graph optimization (FGO) algorithm that integrates Global Navigation Satellite System (GNSS) and pedestrian dead reckoning (PDR) data for pedestrian positioning. It incorporates road-anchor constraints, a turning-point-based anchor-matching method, and a coarse-to-fine optimization strategy to improve the positioning accuracy. GNSS provides global reference positions, PDR offers precise relative motion constraints through accurate heading estimation, and anchor factors further enhance localization accuracy by leveraging known geometric features. We collected data using a smartphone equipped with a four-camera module and conducted tests in representative urban environments. Experimental results demonstrate that the proposed anchor-aided FGO-GNSS/PDR algorithm achieves robust and accurate positioning, effectively supporting video-based map construction in complex urban settings. With anchor constraints, the mean horizontal positioning error was reduced by 42% to 65% and the maximum error by 38% to 76% across all datasets. In this study, the mean horizontal positioning error was 1.36 m.
远程视力辅助（RSA）系统通过将视障人士（VIP）与远程有视力的代理人连接起来，为他们提供实时指导，以方便日常出行。然而，陌生的环境常常使代理人的决策变得复杂，并可能导致视障人士产生焦虑，从而降低所提供援助的效果。为应对这一挑战，本文提出了一种基于视频的地图辅助方法。通过预先录制行人路径视频并将其与地理位置对齐，该系统实现了路线预览并增强了导航指导。本研究引入了一种因子图优化（FGO）算法，该算法集成了全球导航卫星系统（GNSS）和行人航位推算（PDR）数据用于行人定位。它纳入了道路锚点约束、基于转折点的锚点匹配方法以及从粗到精的优化策略，以提高定位精度。GNSS提供全球参考位置，PDR通过精确的航向估计提供精确的相对运动约束，而锚点因子通过利用已知的几何特征进一步提高定位精度。我们使用配备四摄像头模块的智能手机收集数据，并在具有代表性的城市环境中进行测试。实验结果表明，所提出的锚点辅助FGO - GNSS/PDR算法实现了稳健且精确的定位，有效地支持了复杂城市环境中基于视频的地图构建。在所有数据集中，有了锚点约束后，平均水平定位误差降低了42%至65%，最大误差降低了38%至76%。在本研究中，平均水平定位误差为1.36米。
