POINav-Bench provides the first high-fidelity real-world benchmark for POI-goal VLN using 3DGS reconstructions of 126k m² with 163 POIs, supported by a Brain-Action framework and 70K real signage-entrance dataset.
Socialnav: Training human-inspired foundation model for socially-aware embodied navigation
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AsyncShield restores VLA geometric intent from latency via kinematic pose mapping and uses PPO-Lagrangian to balance tracking with LiDAR safety constraints in a plug-and-play module.
ABot-Explorer unifies online exploration and hierarchical semantic memory construction via VLM-distilled navigational affordances for improved embodied navigation efficiency.
ABot-Claw is an embodied software layer that adds unified robot scheduling, cross-embodiment visual memory, and critic-driven replanning on top of OpenClaw to support persistent multi-robot execution from natural-language goals.
citing papers explorer
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POINav: Benchmarking and Enhancing Final-Meters Arrival in Real-World Vision-Language Navigation
POINav-Bench provides the first high-fidelity real-world benchmark for POI-goal VLN using 3DGS reconstructions of 126k m² with 163 POIs, supported by a Brain-Action framework and 70K real signage-entrance dataset.
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AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation
AsyncShield restores VLA geometric intent from latency via kinematic pose mapping and uses PPO-Lagrangian to balance tracking with LiDAR safety constraints in a plug-and-play module.
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Explore Like Humans: Autonomous Exploration with Online SG-Memo Construction for Embodied Agents
ABot-Explorer unifies online exploration and hierarchical semantic memory construction via VLM-distilled navigational affordances for improved embodied navigation efficiency.
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ABot-Claw: A Foundation for Persistent, Cooperative, and Self-Evolving Robotic Agents
ABot-Claw is an embodied software layer that adds unified robot scheduling, cross-embodiment visual memory, and critic-driven replanning on top of OpenClaw to support persistent multi-robot execution from natural-language goals.