Finder: Agentic Closed-Loop Object Finding for Embodied Grounding

arXiv:2609.18058 · cs.CV · Submitted 2026-09-16 · Read on arXiv

cs.CV

Submitted: 2026-09-16

Updated: 2026-09-16

Project page: https://finder-vln.github.io

Terminology

• Grounding — 41× in this paper · explained in 3 episodes
• Benchmark — 16× in this paper · explained in 2 episodes
• Verification — 15× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Verifier — 6× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Downstream Tasks — 4× in this paper · explained in 2 episodes
• Embodied AI — 4× in this paper · explained in 2 episodes
• RAG — 4× in this paper · explained in 3 episodes
• Affordance — 3× in this paper · explained in 1 episode
• Task Planning — 3× in this paper · explained in 2 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Agentic Loop — 2× in this paper · explained in 1 episode
• Agentic System — 2× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Visual Grounding — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Active Exploration — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes

Sources

• SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning
• Vision to Geometry: 3D Spatial Memory for Sequential Embodied MLLM Reasoning and Exploration
• Describe Anything Anywhere At Any Moment
• EmbodiedRAG: Dynamic 3D Scene Graph Retrieval for Efficient and Scalable Robot Task Planning
• RAG-3DSG: Enhancing 3D Scene Graphs with Re-Shot Guided Retrieval-Augmented Generation
• INHerit-SG: Incremental Hierarchical Semantic Scene Graphs with RAG-Style Retrieval
• Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI
• ASHiTA: Automatic Scene-grounded HIerarchical Task Analysis
• Hydra: A Real-time Spatial Perception System for 3D Scene Graph Construction and Optimization
• ZING-3D: Zero-shot Incremental 3D Scene Graphs via Vision-Language Models
• Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments
• Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
• Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation
• MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation
• SAM 3: Segment Anything with Concepts
• FSR-VLN: Fast and Slow Reasoning for Vision-Language Navigation with Hierarchical Multi-modal Scene Graph
• Task-oriented Sequential Grounding and Navigation in 3D Scenes

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