ROCVLGJun 12

VANDERER: Map-Free Exploration using Future-Aware and Visual-Curiosity-Guided Diffusion Policy

arXiv:2606.148797.3
Predicted impact top 60% in RO · last 90 daysOriginality Incremental advance
AI Analysis

It addresses the challenge of efficient exploration for mobile agents with limited sensors (monocular cameras), offering a practical solution for real-world deployment.

VANDERER introduces a map-free exploration framework using a Visual Curiosity Module to guide diffusion policies with monocular images, achieving 13.4% more area explored than NoMaD in simulated environments.

Mobile agents require efficient exploration strategies to map unseen environments and autonomously plan tasks. Traditional methods rely on generating occupancy maps and optimizing the sequence in which unexplored regions are visited. However, in sensor-constrained settings, such as those limited to monocular cameras, generating accurate occupancy maps is challenging. To address this, we propose VANDERER, an exploration framework that leverages a Visual Curiosity Module (VCM) to guide pre-trained diffusion policies using only monocular image data. This curiosity module predicts the outcomes of proposed actions via a navigation world model and evaluates them through a curiosity cost. The cost then guides the diffusion process toward generating actions that maximize exploration. Evaluated across diverse simulated environments, VANDERER consistently outperforms established baselines, exploring an average of 13.4% more area than NoMaD. Our results reveal a direct correlation between visual and geometric curiosity in outdoor environments, demonstrating that VANDERER can effectively leverage this relationship for efficient exploration using sensor-constrained agents.

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