# Multimodal Perception for Goal-oriented Navigation: A Survey

arXiv: https://arxiv.org/abs/2504.15643 · HTML: https://mlsanity.com/paper/2504.15643/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2025.

## Built on by (most cited first, 2 of 2)

- [POINav: Benchmarking and Enhancing Final-Meters Arrival in Real-World Vision-Language Navigation](https://mlsanity.com/paper/2605.28237/) (2026)
- [GG-Nav: Goal-oriented Grounding Chain-of-Thought Elicits Reasoning in Navigation Foundation Models](https://mlsanity.com/paper/2610.14541/) (2026)

## Abstract (arXiv)

Goal-oriented navigation presents a fundamental challenge for autonomous systems, requiring agents to navigate complex environments to reach designated targets. This survey offers a comprehensive analysis of multimodal navigation approaches through the unifying perspective of inference domains, exploring how agents perceive, reason about, and navigate environments using visual, linguistic, and acoustic information. Our key contributions include organizing navigation methods based on their primary environmental reasoning mechanisms across inference domains; systematically analyzing how shared computational foundations support seemingly disparate approaches across different navigation tasks; identifying recurring patterns and distinctive strengths across various navigation paradigms; and examining the integration challenges and opportunities of multimodal perception to enhance navigation capabilities. In addition, we review approximately 200 relevant articles to provide an in-depth understanding of the current landscape.