mirror of
https://github.com/ruvnet/RuView
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rUv
8d64434d21
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).
85 lines
2.5 KiB
TOML
85 lines
2.5 KiB
TOML
[package]
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name = "ruview-swarm"
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version = "0.1.0"
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edition = "2021"
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description = "RuView drone swarm control system — hierarchical-mesh topology, Raft consensus, MARL, CSI sensing integration (ADR-148)"
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license = "Apache-2.0"
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# Publishing disabled until: (1) PR #862 merges, (2) internal path-deps are
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# published in dependency order, (3) export-control sign-off on the ITAR-gated
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# coordination features (USML Category VIII(h)(12)). Flip to true deliberately.
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publish = false
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[features]
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default = []
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# ITAR/USML Category VIII(h)(12): swarming coordination features.
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# Must not be enabled in international distributions without export counsel review.
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itar-unrestricted = []
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mavlink = ["dep:mavlink"]
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ros2-dds = []
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onnx = ["dep:ort"]
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simulation = []
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demo = ["simulation"]
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full = ["mavlink", "onnx", "demo", "itar-unrestricted"]
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ruflo = ["dep:reqwest", "dep:serde_json"]
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# Heavy GPU-capable MARL training (real Candle autodiff PPO). Off by default so
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# the default build stays light and the existing test suite keeps passing.
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train = ["dep:candle-core", "dep:candle-nn"]
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cuda = ["candle-core/cuda", "candle-nn/cuda"]
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[dependencies]
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wifi-densepose-core = { path = "../wifi-densepose-core" }
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# Serialization
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serde = { version = "1", features = ["derive"] }
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serde_json = { version = "1", optional = true }
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toml = "0.8"
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# Async runtime
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tokio = { version = "1", features = ["full"] }
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async-trait = "0.1"
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# MAVLink v2 (optional)
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mavlink = { version = "0.13", optional = true }
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# ONNX Runtime (optional — for MARL actor inference)
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ort = { version = "2.0.0-rc.11", optional = true }
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# Candle 0.9 — real autodiff PPO training (optional, behind `train` feature).
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candle-core = { version = "0.9", default-features = false, optional = true }
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candle-nn = { version = "0.9", default-features = false, optional = true }
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# HTTP client (optional — for Ruflo HTTP backend)
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reqwest = { version = "0.12", features = ["json"], optional = true }
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# Crypto — MAVLink v2 HMAC-SHA256 signing
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hmac = "0.12"
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sha2 = "0.10"
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# Error handling
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thiserror = "2.0"
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# Logging
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tracing = "0.1"
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# Numerics
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nalgebra = "0.33"
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rand = "0.8"
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[dev-dependencies]
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criterion = { version = "0.5", features = ["html_reports"] }
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tokio-test = "0.4"
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[[bench]]
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name = "swarm_bench"
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harness = false
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# MARL training binary — requires the `train` feature (Candle autodiff).
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# Excluded from the default build so `cargo test`/CI stay light.
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[[bin]]
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name = "train_marl"
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required-features = ["train"]
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# ADR-149 Stage-1 evaluation CLI — pure Rust, no special feature needed.
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[[bin]]
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name = "eval_swarm"
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