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3 Commits
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 ruv
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29e698a05c |
fix(ruview-swarm): clippy manual_is_multiple_of in lawnmower planner
CI `clippy (-D warnings, --no-deps)` failed on patterns.rs:131 — `row % 2 == 0` is flagged by clippy::manual_is_multiple_of. Use `row.is_multiple_of(2)` (identical even-row check). Both CI clippy variants (--no-default-features and --features full,train) now pass. Co-Authored-By: claude-flow <ruv@ruv.net> |
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rUv
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8d64434d21 |
feat(swarm): ADR-149 evaluation harness — GDOP, IQM+bootstrap CI, noise sweep (#875)
Stage-1 kinematic evaluator per ADR-149 (peer-reviewed). Pure Rust, no new deps. evals/: - gdop.rs: 2D Geometric Dilution of Precision ((HᵀH)⁻¹ trace-sqrt); None for <2 observers or collinear/singular geometry - stats.rs: IQM (Agarwal 2021) + 95% stratified-bootstrap CI (deterministic LCG) + probability_of_improvement - metrics.rs: EpisodeMetrics + AggregateMetrics::from_strata (IQM±CI, seed-stratified) - runner.rs: seeded kinematic rollout (FlightPattern-driven), seed×episode matrix, 3σ×3κ default noise sweep (Gaussian amplitude × von Mises phase) - report.rs + eval_swarm bin: generates evals/RESULTS.md leaderboard RESULTS.md surfaces the real coverage-vs-localization-precision trade-off via GDOP: partitioned wins coverage (100%) but single-drone sightings (GDOP 0 → 7.0m); pheromone gets multistatic fusion (GDOP 1.6 → 4.1m). Wi2SAR 5m paper-baseline row included. Stage-2 (Gazebo/PX4 SITL false-alarm + collision on median seeds) is documented follow-on. Tests: 116 default / 133 full+train (+13 eval tests), 0 failed. Clippy clean (-D warnings). |
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rUv
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0d3d835bf8 |
feat(swarm): add ruview-swarm crate — drone swarm control system (ADR-148) (#862)
* 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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