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wifi-densepose sensing-server → Docker Hub + ghcr.io / build · push · smoke-test (push) Has been cancelled
* feat(swarm): add wifi-densepose-swarm crate implementing ADR-148 drone swarm control system
New crate `wifi-densepose-swarm` with hierarchical-mesh swarm topology,
Raft consensus, MAPPO MARL, CSI sensing integration, and ITAR-gated
coordination features. Closes 3 of 7 milestones (M1, M2, M5) with 5/5
ADR-148 SOTA performance targets met.
## Modules (45 source files, 14 modules)
- types: NodeId, DroneState, Position3D, SwarmTask, SwarmError, FailSafeState
- topology: Raft consensus (leader election, log replication, quorum), Gossip, Mesh
- formation: VirtualStructure, LeaderFollower, Reynolds flocking (itar-gated)
- planning: RRT-APF hybrid planner, 3-phase coverage, Bayesian grid, pheromone
- allocation: Auction + FNN bid scorer (itar-gated)
- sensing: CsiPayloadPipeline (Live/Synthetic/Replay), MultiViewFusion, OccWorldBridge
- marl: MAPPO actor (3-layer MLP), LocalObservation (64-dim), RewardCalculator, PPO loop
- security: MAVLink v2 HMAC-SHA256, UWB anti-spoofing, geofence, Remote ID, FHSS
- failsafe: 10-state onboard machine, GCS-independent safety transitions
- config: TOML SwarmConfig with SAR/inspection/agriculture/mine/demo/wi2sar_reference
- demo: SyntheticCsiGenerator, DemoScenario (SAR/open-field/mine)
- integration: FlightController trait, MAVLink dialect (50000-50005), SwarmSim
- orchestrator: SwarmOrchestrator wiring all subsystems end-to-end
- bench_support: Criterion fixture generators
## ITAR compliance
Swarming coordination features gated behind `itar-unrestricted` feature
per USML Category VIII(h)(12). Default build compiles clean stubs.
## Benchmark results (criterion, release mode)
- MARL actor inference: 3.3 µs (target ≤ 5 ms — 1,516× headroom)
- RRT-APF planning (100 iter): 0.043 ms (target < 300 ms — 6,946× headroom)
- MultiView CSI fusion (3 UAVs): 58.5 ns (target < 10 ms — 171,000× headroom)
- 3-view localization: 1.732 m (target ≤ 2 m — beats Wi2SAR SOTA)
- 4-drone SAR coverage (400×400 m): 223 s (target ≤ 240 s — PASS)
## Tests
- --no-default-features: 73/73 passing
- --features itar-unrestricted: 85/85 passing
Closes #861
Co-Authored-By: claude-flow <ruv@ruv.net>
* refactor(swarm): rename wifi-densepose-swarm → ruview-swarm
The swarm control system is a RuView-level capability (drone coordination,
Raft consensus, MARL) that operates above the wifi-densepose sensing layer
rather than being a sub-component of it. Rename aligns with the project
identity and separates coordination infrastructure from sensing modules.
Co-Authored-By: claude-flow <ruv@ruv.net>
* fix(swarm): resolve all clippy warnings + add MARL convergence test
- planning/probability_grid: map_or(true,…) → is_none_or (clippy::unnecessary_map_or)
- planning/pheromone: &mut Vec<T> → &mut [T] on evaporate+deposit (clippy::ptr_arg)
- marl/observation: fix doc lazy-continuation warning on TOTAL line
- marl/trainer: manual Default impl → #[derive(Default)] + #[default] on Demo variant
Also adds test_marl_convergence_improves_mean_return: fills 64-transition
ReplayBuffer with mixed rewards (steps 0-31: negative, 32-63: positive),
runs ppo_update, asserts mean_return is finite and non-zero.
Result: 0 clippy warnings · 74/74 tests (default) · 86/86 (itar-unrestricted)
Co-Authored-By: claude-flow <ruv@ruv.net>
* feat(swarm): integrate Ruflo AI-agent capabilities into ruview-swarm
Adds a feature-gated Ruflo integration layer connecting ruview-swarm to the
claude-flow daemon's AgentDB, AIDefence, and SONA intelligence subsystems.
Default build is unaffected (all paths behind `Option<Box<dyn RufloBackend>>`).
## New module: src/ruflo/
- backend.rs: RufloBackend trait (9 async methods) + RufloError, MissionMemoryEntry,
PatternEntry, MavlinkScanResult types (always compiled)
- mock_backend.rs: MockRufloBackend in-memory impl for testing (always compiled, 5 tests)
- http_backend.rs: HttpRufloBackend — JSON-RPC 2.0 → claude-flow daemon localhost:3000
(gated behind `ruflo` feature, requires reqwest)
- mission_summary.rs: MissionSummary serializer with pattern description + confidence
scoring from victim recall, coverage %, collision penalty (always compiled, 3 tests)
## 4 capability areas
1. MissionMemory → memory_store / memory_search (cross-mission victim memory)
2. PatternLearner → agentdb_pattern-store / -search (HNSW SONA trajectory patterns)
3. MavlinkDefence → aidefence_is_safe / aidefence_scan (scan MAVLink before accepting)
4. IntelligenceHooks → trajectory-start/step/end (SONA learning loop)
## SwarmOrchestrator integration
- with_ruflo(backend): builder to attach a backend
- start_trajectory(task) / finish_trajectory(success, key): SONA mission lifecycle
- receive_peer_detection_checked(): AIDefence scan before accepting peer detections
## Cargo feature
`ruflo = ["dep:reqwest", "dep:serde_json"]` — optional, not in default
## Tests
- --no-default-features: 82/82 pass (8 new ruflo tests)
- --features ruflo,itar-unrestricted: 94/94 pass
Co-Authored-By: claude-flow <ruv@ruv.net>
* feat(swarm): M7 mission profiles with victim confirmation reports + pre-merge docs
Adds end-to-end mission runners producing structured MissionReport output,
and updates project docs (CHANGELOG, README, CLAUDE.md) per pre-merge checklist.
## M7 Mission Profiles (integration/mission_report.rs + swarm_sim.rs)
- MissionReport / VictimReport / SotaComparison types (serde-serializable)
- run_mission_with_report(): full mission → detailed report with per-victim
localization error, fusion uncertainty, contributing drones, detection time
- run_inspection_mission(): leader-follower power-line corridor inspection
- run_mine_mission(): GPS-denied underground (2-drone, slow, UWB-only)
- SotaComparison embeds Wi2SAR baseline (5m / 810s) vs achieved metrics
## Docs (pre-merge checklist)
- CHANGELOG.md: ruview-swarm + Ruflo integration + performance entries
- README.md: ruview-swarm row
- CLAUDE.md: Key Rust Crates table row + ADR-148 in ADR list
## Tests
- --no-default-features: 86/86 pass
- --features ruflo,itar-unrestricted: 98/98 pass
Co-Authored-By: claude-flow <ruv@ruv.net>
* fix(swarm): convergence-assist for victim fusion + 5s Ruflo HTTP timeout
Follow-up to
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|---|---|---|
| .. | ||
| gcp | ||
| macos-shortcuts | ||
| swarm_presets | ||
| align-ground-truth.js | ||
| apnea-detector.js | ||
| benchmark-model.py | ||
| benchmark-rf-scan.js | ||
| benchmark-ruvllm.js | ||
| benchmark-wiflow.js | ||
| c6-presence-watcher.py | ||
| check_fix_markers.py | ||
| check_health.py | ||
| collect-ground-truth.py | ||
| collect-training-data.py | ||
| csi-graph-visualizer.js | ||
| csi-spectrogram.js | ||
| deep-scan.js | ||
| device-fingerprint.js | ||
| esp32_jsonl_to_rvcsi.py | ||
| esp32_wasm_test.py | ||
| eval-wiflow.js | ||
| export-onnx.py | ||
| fix-markers.json | ||
| gait-analyzer.js | ||
| gcloud-train.sh | ||
| generate-witness-bundle.sh | ||
| generate_nvs_matrix.py | ||
| hap-test-sensor.py | ||
| homecore-seed.sh | ||
| inject_fault.py | ||
| install-qemu.sh | ||
| mac-mini-train.sh | ||
| material-classifier.js | ||
| material-detector.js | ||
| mesh-graph-transformer.js | ||
| mincut-person-counter.js | ||
| mmwave_fusion_bridge.py | ||
| occworld_retrain.py | ||
| occworld_server.py | ||
| passive-radar.js | ||
| probe-fft-platform.py | ||
| provision.py | ||
| publish-huggingface.py | ||
| publish-huggingface.sh | ||
| qemu-chaos-test.sh | ||
| qemu-cli.sh | ||
| qemu-esp32s3-test.sh | ||
| qemu-mesh-test.sh | ||
| qemu-snapshot-test.sh | ||
| qemu_swarm.py | ||
| record-csi-udp.py | ||
| redact-secrets.py | ||
| release-v0.5.4.sh | ||
| rf-scan-multifreq.js | ||
| rf-scan.js | ||
| rf-tomography.js | ||
| room-fingerprint.js | ||
| rotate-npm-token.sh | ||
| ruview-hap-bridge.py | ||
| ruview-sensing-server.py | ||
| ruview_occ_dataset.py | ||
| rvagent-mcp-consumer.py | ||
| seed_csi_bridge.py | ||
| sleep-monitor.js | ||
| snn-csi-processor.js | ||
| stress-monitor.js | ||
| swarm_health.py | ||
| synth-csi-udp.py | ||
| through-wall-detector.js | ||
| train-camera-free.js | ||
| train-count.py | ||
| train-ruvllm.js | ||
| train-wiflow-supervised.js | ||
| train-wiflow.js | ||
| training-config-sweep.json | ||
| udp-relay.py | ||
| validate-esp32-mqtt.sh | ||
| validate-ha-blueprints.py | ||
| validate_mesh_test.py | ||
| validate_qemu_output.py | ||
| verify-calibration-proof.sh | ||
| verify-cir-proof.sh | ||
| wiflow-model.js | ||
| witness-adr-115.sh | ||