ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation

• URL: http://arxiv.org/abs/2602.11598v1
• Date: Thu, 12 Feb 2026 05:30:20 GMT
• Title: ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation
• Abstract summary: We introduce ABot-N0, a unified Vision-Language-Action (VLA) foundation model that achieves a Grand Unification'' across 5 core tasks.<n>ABot-N0 utilizes a hierarchical Brain-Action'' architecture, pairing an LLM-based Cognitive Brain for semantic reasoning with a Flow Matching-based Action Expert for precise, continuous trajectory generation.
• Score: 50.35621223011076
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Embodied navigation has long been fragmented by task-specific architectures. We introduce ABot-N0, a unified Vision-Language-Action (VLA) foundation model that achieves a ``Grand Unification'' across 5 core tasks: Point-Goal, Object-Goal, Instruction-Following, POI-Goal, and Person-Following. ABot-N0 utilizes a hierarchical ``Brain-Action'' architecture, pairing an LLM-based Cognitive Brain for semantic reasoning with a Flow Matching-based Action Expert for precise, continuous trajectory generation. To support large-scale learning, we developed the ABot-N0 Data Engine, curating 16.9M expert trajectories and 5.0M reasoning samples across 7,802 high-fidelity 3D scenes (10.7 $\text{km}^2$). ABot-N0 achieves new SOTA performance across 7 benchmarks, significantly outperforming specialized models. Furthermore, our Agentic Navigation System integrates a planner with hierarchical topological memory, enabling robust, long-horizon missions in dynamic real-world environments.

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