CognitiveReality: LLMエージェントによるロボット非依存の意味的ガウスマッピングと没入型協調VRテレオペレーション
CognitiveReality: Robot-Agnostic Semantic Gaussian Mapping with an LLM Agent for Immersive Collaborative VR Teleoperation
ロボットのRGB-D映像から意味的に索引付けされたガウス-TSDFマップを生成し、VR上の操作者とツール利用型言語エージェントが共有して、音声やポインティングをロボット行動に変換するシステムを提案。2台の四足歩行ロボットで実証した。
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著者: Timofei Kozlov, Dmitrii Maliukov, Andrey Marchenko, Dmitrii Plotnikov, Miguel Altamirano Cabrera, Dzmitry Tsetserukou
分類: cs.RO
原文アブストラクト
A photorealistic 3D view tells a teleoperator where a robot is, but not what the scene contains, how well each object has been observed, or how to turn pointing and speech into robot action. CognitiveReality turns a robot's RGB-D stream into a live, semantically indexed Gaussian-TSDF map shared by an operator in virtual reality and a tool-using language agent. One mapper binary serves any platform through configuration alone: it ingests poses from robot SLAM, joint kinematics, motion capture or an inline visual tracker, bridges localization outages with a shadow tracker and keyframe-anchored PnP, and maintains open-vocabulary instance identities with per-object quality at 2 Hz. Speech and controller rays are grounded against persistent scene objects through validated typed tools and operator-confirmed robot actions. In the controlled agent evaluation, the deployed local Qwen3-VL-8B router reaches 81.24\% tool exact match, while merge-aware replay correctly redirects 101 absorbed object identifiers. On robot data CognitiveReality exceeds a Gaussian-plus-SDF baseline by 2-8 dB; pose error through 5-40 s SLAM outages stays within 1-8 cm. Deployed live on two quadrupeds, the agent executed 26 of 30 navigation requests and 20 of 20 re-observation requests, raising object quality by 2-5 dB.