superxslam/SuperMap - 仓库详情

AI 仓库情报摘要

FR-AI / ANALYSIS

为什么值得关注

它引入了活体空间记忆，可在遮挡和场景变化中维持物体标识的一致性，无需训练即可支持推理与动作，并在校园环境中完成了连续 2 小时的实际部署验证。

适合谁使用

具身 AI 研究人员
构建导航系统的机器人工程师
SLAM 与建图从业者
视觉语言导航与 VLA 智能体开发者

典型使用场景

移动机器人实时物体级建图
动态环境下的视觉语言导航
需要物体时间历史的长时推理任务
离线数据集处理与通过 ROS2 的实时部署

项目优势

免训练且模型无关，支持多种开放词汇检测器
完全在线运行，单代码库即可在机器人硬件上实时工作
生成可查询的 4D 场景图，包含空间和时间信息
经过校园连续 2 小时实际部署验证

使用前须知

需要 Ubuntu 22.04/24.04 和至少 16 GB 显存的 NVIDIA GPU
代码尚未发布，计划在 RSS 2026 会后公开
实时模式依赖 ROS2 Jazzy，限制了非 ROS 环境的使用

README 快速开始

SuperMap: A Living Spatial Memory for Embodied AI RSS 2026

AirLab, Carnegie Mellon University

Announcement: The code will be released after RSS.

News

2026-07-15: Project website and teaser video are now live.
2026-07-15: Initial README and project overview published.

SuperMap is a living spatial memory for embodied AI. It perceives the world, remembers its evolution, and supports reasoning and action. It is a training-free spatio-temporal SLAM system that builds a persistent semantic world model. It fuses high-frequency geometric SLAM with asynchronous open-vocabulary perception, producing a 4D scene graph: a queryable map carrying spatial and temporal information for every object, enabling visual-language navigation and long-horizon reasoning on real robots.

Highlights

👀 Perceive — Stable identities across occlusions and scene changes via 3D-aware instance association.
🧠 Remember — persistent object identities capture long-term scene evolution.
💡 Reason — a queryable 4D scene graph supports spatial and tempora reasoning.
🤖 Act — spatial memory naturally grounds VLN, VLA, and future embodied AI systems.
🔌 Model-agnostic — works with Grounding DINO, YOLOE, boxer pre-baked detections.
⚡ Fully online — real-time on robot hardware; runs offline on datasets or live via ROS2 from one codebase.
🏫 Field-proven — continuous 2-hour deployment across the CMU campus (interactive demo).

Requirements

Ubuntu 22.04 / 24.04, NVIDIA GPU with ≥ 16 GB VRAM, Python ≥ 3.10
ROS2 Jazzy workspace for live mode

Setup

git clone https://github.com/superxslam/SuperMap.git
cd SuperMap
conda create -n supermap python=3.11 && conda activate supermap

pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu124
conda install cuda -c nvidia/label/cuda-12.4.0
export CUDA_HOME=$(dirname $(dirname $(which nvcc)))

pip install -r requirements.txt
python -m spacy download en_core_web_sm

Run (offline)

python examples/prepare_example_dataset.py   # download example dataset (one-time)
python examples/example.py                   # run the mapping pipeline

项目描述

SuperMap is a living spatial memory for embodied AI — it perceives the world, remembers its evolution, and supports reasoning and action.

SuperMap