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ruview-mmwave 精选

Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect, v0.5.0+). Use when the deployment includes a millimetre-wave radar alongside or instead of WiFi CSI.

编码 Claude CodeCodex CLIMCP 客户端 MIT 9.8 万
在 GitHub 打开

安装方式

cp -r plugins/ruview/skills/ruview-mmwave ~/.claude/skills/ruview-mmwave

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同，Claude Code 默认是 ~/.claude/skills/

整仓一次性获取：git clone --depth 1 https://github.com/ruvnet/RuView.git

依赖与权限

  • 无需 API Key
  • 无需联网
  • 依赖外部命令：git node python
  • 以上为按正文与 frontmatter 自动推断的信号，仅供参考；安装前建议先阅读原文。
触发场景
instead of WiFi CSI
allowed-tools
Bash Read Write Edit Glob Grep

SKILL.md 正文

来源 ruvnet/RuView@a71634a · 许可 MIT · 内容未修改

RuView mmWave / FMCW Radar

The radio side-channel: 60 GHz and 24 GHz FMCW radar, standalone and fused with WiFi CSI.

Hardware

DevicePortBandProvides~Cost
ESP32-C6 + Seeed MR60BHA2COM4 (typical)60 GHz FMCWHeart rate, breathing rate, presence~$15
HLK-LD2410—24 GHz FMCWPresence + distance (gated zones)~$3

The C6 is RISC-V and can run the radar pipeline; it is not a WiFi-CSI node (use an ESP32-S3 for CSI). LD2410 is a UART module wired to a host or to the C6.

1. Firmware with mmWave fusion (v0.5.0+)

The ESP32 firmware auto-detects an attached MR60BHA2 or LD2410 and emits 48-byte fused vitals records (CSI-derived + radar-derived, reconciled). Binary is ~12 KB larger than the CSI-only build. Build/flash as in ruview-hardware-setup (Windows: Python-subprocess; ESP-IDF v5.4 ≠ Git Bash). Recommended stable firmware tag: v0.5.0-esp32 or later — see docs/user-guide.md release table.

# Provision the radar/fusion node (same provision.py; the firmware probes for the radar on boot)
python firmware/esp32-csi-node/provision.py --port COM8 --ssid "WiFi" --password "secret" --target-ip 192.168.1.20
# Confirm: serial monitor should report which radar was detected and start emitting fused vitals

2. mmWave ↔ WiFi-CSI fusion bridge (host side)

python scripts/mmwave_fusion_bridge.py            # bridges radar HR/BR + CSI → unified spatial model
node scripts/passive-radar.js                     # passive-radar style processing for exploration

The 3D point-cloud demo fuses camera depth (MiDaS) + WiFi CSI + mmWave radar → unified spatial model (~22 ms pipeline, 19K+ pts/frame; ADR-094). Drive it with scripts/mmwave_fusion_bridge.py plus the point-cloud front-end.

3. Standalone radar use

  • MR60BHA2 (60 GHz) — best for contactless vitals on a (near-)stationary subject: blood pressure proxy, heart rate, breathing rate; $15 hardware, no wearable. See examples/medical/README.md.
  • LD2410 (24 GHz) — best for cheap presence + coarse distance / gated zones; complements CSI presence (PIR-style fusion) for higher confidence.

4. When to use mmWave vs. WiFi CSI

SituationPrefer
Contactless vitals, subject stationary, line of sightMR60BHA2 (cleaner HR/BR than CSI alone)
Cheap, robust presence / occupancy in a defined zoneLD2410 (or LD2410 + CSI)
Through-wall presence / activity, no line of sightWiFi CSI (mmWave doesn't penetrate walls)
Pose / skeletonsWiFi CSI (WiFlow) — mmWave doesn't do this here
Highest-confidence vitalsFusion — 48-byte fused vitals reconcile CSI + radar
Volumetric 3DFusion — camera depth + CSI + mmWave point cloud

Reference

  • Hardware tables: README.md, docs/user-guide.md (release table — v0.5.0 mmWave fusion notes, binary sizes)
  • scripts/mmwave_fusion_bridge.py, scripts/passive-radar.js
  • examples/medical/README.md (60 GHz mmWave vitals)
  • ADR-094 (point-cloud GitHub Pages deployment)
  • Validate firmware changes with the QEMU helpers and ruview-verify

质量与来源

所属仓库
ruvnet/RuView
仓库星标
9.8 万
最近更新
今天
采集时间
今天
commit
a71634ae8a60
内容指纹
sha256:d11b818564c30e2
文件路径
plugins/ruview/skills/ruview-mmwave/SKILL.md

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