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Pins operator-link transport to gRPC server-streaming (closes architecture Q2 in favour of gRPC). Adds first-time tonic / prost / tonic-build infrastructure to the workspace; uses protoc-bin-vendored so neither dev machines nor CI need system protoc installed. Design — back-pressure lives in the per-topic tokio::sync::broadcast ring, drained directly by the tonic-streamed response via BroadcastStream + StreamMap. No intermediate mpsc buffer that could absorb back-pressure invisibly. Slow client overrun -> Lagged(n) event -> per-(client_id, topic) drop counter incremented; healthy clients on the same topic are unaffected. Service surface — Subscribe(SubscribeRequest) -> stream TelemetryMessage; five topics (TelemetrySample, GimbalState, DetectionEvent, MovementCandidate, MapObjectsBundle); empty topics list defaults to subscribe-all; empty client_id rejected; stream drop decrements subscribed_clients via StreamGuard. TelemetrySink push_detections is now real; push_frame still NotImplemented(AZ-676 video path). Tests — 6 unit + 5 integration (AC-1..AC-3 via in-process gRPC client, plus subscribe-all default + empty-client_id rejection). Clippy on telemetry_stream clean. Pre-existing mission_executor ac3 test polling race surfaces more reliably under the new tonic build pressure; documented as _docs/_process_leftovers/2026-05-20_mission_executor_ac3_flake.md and unchanged by this batch. Co-authored-by: Cursor <cursoragent@cursor.com>
autopilot
Onboard mission executor for the AZAION reconnaissance UAV. Single Rust binary; runs on
NVIDIA Jetson Orin Nano Super (aarch64). See _docs/02_document/architecture.md for the
authoritative system design.
Layout
crates/
shared/ # canonical DTOs, config, error, health, observability, clock, contracts
autopilot/ # binary crate — runtime composition root + /health endpoint
mavlink_layer/ # hand-rolled MAVLink v2 transport
mission_client/ # missions API REST client + MapObjects sync
frame_ingest/ # RTSP pull + decode
detection_client/ # bi-directional gRPC to ../detections
movement_detector/ # ego-motion-compensated residual-motion clustering
semantic_analyzer/ # Tier 2 — primitive graph + ROI CNN
vlm_client/ # Tier 3 — optional NanoLLM/VILA local IPC
mapobjects_store/ # H3-indexed on-device map + ignored items
gimbal_controller/ # ViewPro A40 UDP control
scan_controller/ # central typed state machine (ZoomedOut/ZoomedIn/TargetFollow)
operator_bridge/ # POI surface + operator command authentication
mission_executor/ # multirotor + fixed-wing FSMs + geofence + failsafe
telemetry_stream/ # always-on uplink to Ground Station
config/ # TOML config per environment (dev / staging / prod)
deploy/systemd/ # on-airframe native systemd unit (Option A)
fixtures/ # replay clips (RTSP, MAVLink, missions, detections)
tests/e2e/ # workspace-level blackbox scenarios
benches/ # NFR benchmark-gate harness
Build
# Host-arch build + tests
cargo build --workspace
cargo test --workspace --locked
# Optional VLM feature path
cargo build --workspace --features vlm
# No-default-features path (enforces the VLM optionality contract)
cargo build --workspace --no-default-features
cargo test --workspace --no-default-features
# aarch64 cross-build (CI uses cargo-zigbuild; locally `cross` also works)
cargo install --locked cargo-zigbuild
rustup target add aarch64-unknown-linux-gnu
cargo zigbuild --release --target aarch64-unknown-linux-gnu --workspace
Run (dev)
cp .env.example .env
docker compose up -d
# Then inspect:
curl -s http://127.0.0.1:8080/health | jq
Documentation
The full document tree lives under _docs/. Start with:
_docs/00_problem/problem.md— the problem statement_docs/02_document/architecture.md— system architecture_docs/02_document/system-flows.md— sequence diagrams_docs/02_document/components/<name>/description.md— per-component specs_docs/02_document/deployment/{containerization,ci_cd_pipeline,observability}.md
CI
.woodpecker.yml drives the pipeline. Stages: fetch → lint → unit-test → build-arm64 → build-no-vlm → integration-test → sitl-conformance → security-scan → package → sign → publish → benchmark-gate (opt-in).
Description
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