SuperMap: A Spatio-Temporal SLAM System for Visual-Language Navigation
2026-08-24 • Robotics
Robotics
AI summaryⓘ
The authors developed SuperMap, a system that helps robots understand and remember people’s environments over time using language and vision together. It combines detailed 3D mapping with flexible object recognition that works even when things change or move around. SuperMap keeps track of objects consistently by updating their identities and removing outdated info, making it easier for robots to answer questions about their surroundings. They tested it on real robots and released it as open-source for others to use.
Robotic navigationSpatio-temporal mappingSLAMOpen-vocabulary perceptionInstance associationScene graphVision-Language ModelsObject recognitionDynamic environments
Authors
Shibo Zhao, Guofei Chen, Honghao Zhu, Zhiheng Li, Changwei Yao, Nader Zantout, Seungchan Kim, Wenshan Wang, Ji Zhang, Sebastian Scherer
Abstract
Robotic navigation in human environments requires a spatio-temporal semantic representation that can rec- oncile open-vocabulary perception with long-term environmental changes. While foundation models provide strong zero-shot recognition, their predictions are intermittent and view-dependent, and naively integrating them into mapping pipelines leads to identity drift and stale semantics over time. We present SuperMap, a 4D spatio-temporal mapping framework for language-guided navigation that integrates high-frequency geometric SLAM with asynchronous open-vocabulary perception. Our core contribution is a consistency-driven mapping engine that combines 3D-aware instance association/re-activation with a principled existence-and-label confidence update to maintain stable object identities and prune outdated map content under occlusions and scene changes. SuperMap produces a queryable 4D scene-graph representation that interfaces naturally with Vision-Language Models by supporting compositional queries over object semantics, relations, We demonstrate SuperMap on benchmarks and real robots, including dynamic scenes with appearance/disappearance and relocation, and provide ablations and runtime analysis. We release the full system as open-source to provide the community with a deployable baseline for open-vocabulary spatio-temporal mapping. Project website: superodometry.com/supermap.