# Intention Recognition in Real-Time Interactive Navigation Maps

arXiv: https://arxiv.org/abs/2502.17581 · HTML: https://mlsanity.com/paper/2502.17581/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 20 references that are in the map.
- First posted on arXiv 24 Feb 2025.

## Builds on (most cited first, 3 of 3)

- [On the Planning Abilities of Large Language Models : A Critical Investigation](https://mlsanity.com/paper/2305.15771/) (2023)
- [Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation](https://mlsanity.com/paper/1910.03858/) (2019)
- [Elastic Pathing: Your Speed is Enough to Track You](https://mlsanity.com/paper/1401.0052/) (2013)

## Abstract (arXiv)

In this demonstration, we develop IntentRec4Maps, a system to recognise users' intentions in interactive maps for real-world navigation. IntentRec4Maps uses the Google Maps Platform as the real-world interactive map, and a very effective approach for recognising users' intentions in real-time. We showcase the recognition process of IntentRec4Maps using two different Path-Planners and a Large Language Model (LLM). GitHub: https://github.com/PeijieZ/IntentRec4Maps