Summary of Navigation with Vlm Framework: Go to Any Language, by Zecheng Yin and Chonghao Cheng and Lizhen
Navigation with VLM framework: Go to Any Language
by Zecheng Yin, Chonghao Cheng, Lizhen
First submitted to arxiv on: 18 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recently, Vision Large Language Models (VLMs) have shown remarkable capabilities in reasoning with both language and visual data. While many works have leveraged VLMs for navigation in open scenes and vocabularies, they often fall short of fully utilizing the potential or require substantial resources. We introduce Navigation with VLM (NavVLM), a framework that harnesses equipment-level VLMs to enable agents to navigate towards any language goal specific or non-specific in open scenes, emulating human exploration behaviors without prior training. The agent leverages the VLM as its cognitive core to perceive environmental information based on any language goal and provides exploration guidance during navigation until it reaches the target location or area. Our framework achieves state-of-the-art performance in Success Rate (SR) and Success weighted by Path Length (SPL) in traditional specific goal settings, and extends navigation capabilities to any open-set language goal. We evaluate NavVLM in richly detailed environments from the Matterport 3D (MP3D), Habitat Matterport 3D (HM3D), and Gibson datasets within the Habitat simulator. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to find your way around a new city, but instead of using a map or GPS, you use language to navigate. This is what researchers have been working on – creating a way for computers to understand and follow language goals in 3D environments. They’ve developed a new framework called NavVLM that uses special computer models called Vision Large Language Models (VLMs) to help agents find their way around open scenes, just like humans do. The model can be trained to understand any language goal, from finding a specific location to exploring an entire city. This technology has the potential to revolutionize how we interact with computers and the world around us. |
