MCNav: Memory-Aware Dynamic Cognitive Map for Zero-shot Goal-oriented Navigation

• URL: http://arxiv.org/abs/2605.19594v1
• Date: Tue, 19 May 2026 09:39:51 GMT
• Title: MCNav: Memory-Aware Dynamic Cognitive Map for Zero-shot Goal-oriented Navigation
• Abstract summary: MCNav is a memory-aware navigation framework with a dynamic cognitive map.<n>We introduce two memory-aware exploration strategies: goal re-validation and missed goal re-exploration.<n>We evaluate MCNav on the HM3Dv1 and HM3Dv2 datasets across three different tasks.
• Score: 20.5138418643777
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Navigating to instance-level targets in complex environments is a challenging problem. Many existing zero-shot methods achieve strong performance by modeling the entire environment and leveraging large language models for scene understanding. However, such strategies primarily focus on exploring new regions while lacking a deeper exploitation of information from previously explored areas. Consequently, when targets are missed or misidentified within previously visited regions, navigation failures occur frequently. To address these limitations, we propose MCNav, a memory-aware navigation framework with a dynamic cognitive map. This map stores efficiently queryable information about relevant objects in explored areas. Building on this memory structure, MCNav introduces two memory-aware exploration strategies: goal re-validation, which re-assesses previously seen objects to correct matching failures, and missed goal re-exploration, which estimates the likelihood that a target is present in an explored region from contextual cues. These strategies are further stabilized by a blacklist mechanism to prevent repeated errors and a double-check mechanism for high-confidence confirmation. We evaluate MCNav on the HM3Dv1 and HM3Dv2 datasets across three different tasks, where it achieves state-of-the-art performance, particularly on the instance-level goal navigation task.

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