HuMemSLAM: Efficient Human-Inspired Semantic Place Recognition for Robust Visual SLAM
Autonomous systems require reliable place recognition for efficient and effective simultaneous localisation and mapping (SLAM). Traditional geometric visual SLAM approaches rely on low-level features and geometric consistency, but remain vulnerable to perceptual aliasing, where different places appear similar, and perceptual variation, where the same place appears different. Although semantic SLAM and modern learned visual place recognition (VPR) methods improve robustness under challenging perceptual conditions, real-time deployment requires both high retrieval accuracy and low latency. Inspired by human memory and perception, we propose HuMem-VPR, which exploits the bidirectional relati...
| Authors | Mayowa Adebambo, Sebastian Donnelly, Armand Amaritei et al. |
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| Primary category | cs.RO |
| Published | 15 September 2026 |
| Last updated at source | 15 September 2026 |
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