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RNR-Nav: A Real-World Visual Navigation System Using Renderable Neural Radiance Maps

Autor: Kim, Minsoo, Kwon, Obin, Jun, Howoong, Oh, Songhwai

We propose a novel visual localization and navigation framework for real-world environments directly integrating observed visual information into the bird-eye-view map. While the renderable neural radiance map (RNR-Map) shows considerable promise in

Externí odkaz: http://arxiv.org/abs/2410.05621

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Renderable Neural Radiance Map for Visual Navigation

Autor: Kwon, Obin, Park, Jeongho, Oh, Songhwai

We propose a novel type of map for visual navigation, a renderable neural radiance map (RNR-Map), which is designed to contain the overall visual information of a 3D environment. The RNR-Map has a grid form and consists of latent codes at each pixel.

Externí odkaz: http://arxiv.org/abs/2303.00304

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Topological Semantic Graph Memory for Image-Goal Navigation

Autor: Kim, Nuri, Kwon, Obin, Yoo, Hwiyeon, Choi, Yunho, Park, Jeongho, Oh, Songhwai

A novel framework is proposed to incrementally collect landmark-based graph memory and use the collected memory for image goal navigation. Given a target image to search, an embodied robot utilizes semantic memory to find the target in an unknown env

Externí odkaz: http://arxiv.org/abs/2209.08274

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Visually Grounding Language Instruction for History-Dependent Manipulation

Autor: Ahn, Hyemin, Kwon, Obin, Kim, Kyoungdo, Jeong, Jaeyeon, Jun, Howoong, Lee, Hongjung, Lee, Dongheui, Oh, Songhwai

This paper emphasizes the importance of a robot's ability to refer to its task history, especially when it executes a series of pick-and-place manipulations by following language instructions given one by one. The advantage of referring to the manipu

Externí odkaz: http://arxiv.org/abs/2012.08977

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