A pure-text and local AI-based offline navigation method and system

Abstract

This invention discloses an offline navigation method and system based on plain text and local AI. The method parses the user-input text start and end point information using a local offline AI model, combines it with a pre-stored local text-based geographic knowledge base to perform path reasoning, and generates plain text walking steps. The system does not rely on GPS, BeiDou, or other satellite positioning signals or external networks; all calculations and data storage are completed locally on the terminal, and it can generate simulated GPS coordinates and visually assisted navigation. This invention is applicable to scenarios such as signal-free spaces, indoor environments, and visually impaired assistance, and features high privacy, strong stability, and a wide range of applications.

Description

Technical Field

[0001] This invention relates to the fields of offline navigation and local artificial intelligence technology, specifically to a navigation method and system that does not rely on satellite positioning and networks, but achieves path planning solely through pure text interaction and local AI calculation. Background Technology

[0002] Currently, most mainstream navigation methods rely on satellite positioning modules such as GPS and BeiDou, as well as online map data. These methods cannot function properly in scenarios with no signal, signal blockage, or underground spaces. Some offline navigation solutions still require hardware positioning support and cannot perform autonomous path reasoning through purely textual descriptions. Purely textual routes rely on manual memorization, lack standardized and computationally calculable intelligent navigation mechanisms, and are inconvenient and have low accuracy. Therefore, a technical solution is needed that completely eliminates the need for external signals and enables navigation solely through local computation and text interaction. Summary of the Invention

[0003] This invention aims to address the dependence of existing navigation systems on satellite signals, networks, and external maps, providing an offline navigation method and system based on plain text input and local AI. This enables intelligent path planning and text navigation output in environments without positioning or network connectivity. The invention discloses an offline navigation method based on plain text and local AI, comprising the following steps: receiving user-inputted plain text start and end point information; performing semantic parsing of the text information using a local offline AI model to identify the start, end, and related location entities; performing path reasoning and route calculation based on a pre-stored local text-based geographic knowledge base; and generating and outputting walking steps in plain text format. The entire process does not rely on real GPS, BeiDou satellite signals, or external networks. Path reasoning can use simulated GPS coordinates generated by local AI. These coordinates are virtual positioning data, requiring no external signals and independent of real satellite positioning. The text-based geographic knowledge base consists of textual descriptions of roads, landmarks, directions, and distances, and can be manually entered and updated locally without network synchronization. Path reasoning is calculated by the local AI model on the terminal, without data interaction with the cloud, ensuring privacy and offline stability. The output results default to using pure natural language steps, and are also compatible with locally generated simulated images and maps for visualization. All visualizations are synthesized locally and do not rely on external map resources. This invention also discloses a pure text offline navigation system based on local AI, including a text input unit, a local AI inference unit, an offline text geographic knowledge base, a path calculation unit, a text output unit, an image synthesis unit, a simulated map generation unit, and a graphics display unit. The system can operate independently in an environment without external signals, achieving pure text interactive navigation and optional visualization displays.

Claims

1. A pure text and local AI based offline navigation method, characterized in that, include: Receive the start and end points of plain text input by the user; The text is semantically parsed using a local offline AI model to identify location entities; path reasoning is performed based on a locally stored text geographic knowledge base; and plain text step navigation results are generated. The entire process does not rely on real GPS, BeiDou satellite signals, or external networks; the path reasoning can be completed based on simulated GPS coordinates generated by local AI. These simulated GPS coordinates are virtual positioning data, which do not require receiving satellite signals or network data and are independent of real satellite positioning technology.

2. The method of claim 1, wherein, The text-based geographic knowledge base consists of text descriptions of roads, landmarks, directions, and distances, and supports local manual updates.

3. The method of claim 1, wherein, Path reasoning is performed by a local AI model on the terminal without interacting with the cloud.

4. The method of claim 1, wherein, The output results are presented as walking steps in pure natural language by default, and can be used to visualize locally generated simulated images or simulated maps without relying on external networks or real map data.

5. A local AI based pure text offline navigation system characterized by, include: The system includes a text input unit, a local AI reasoning unit, an offline text-based geographic knowledge base, a path calculation unit, a text output unit, an image synthesis unit, a simulated map generation unit, and a graphics display unit. The system is used to perform the method according to any one of claims 1-4.