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uav-array-codesign-rl

# Task brief: drone-hfss-link-codesign

Status: APPROVED   Grader version: v2.0   Owner: Piyush   Date: 2026-10-25

## Capability claim
A pass proves that an agent can jointly solve a coupled electromagnetic structure design problem (3D array geometry, mutual-coupling active impedance, and L-section reactive matching network) and a sequential 6-DoF flight beamforming and link-control problem (body-frame attitude transformations, jammer nulling under active reflection constraints, and thermal/energy/queue management) from physical simulation telemetry. A fail does not distinguish between an electromagnetic mismatch failure and a flight-control failure without inspecting the per-test CTRF breakdown.

## Seed
Inspired by real UAV command-and-control (C2) and telemetry link failures during high-bank maneuvers in contested RF environments:
1. A belly-mounted 2x2 planar dipole array on a conductive carbon-fiber quadrotor airframe exhibits severe scan blindness and high return loss when designed with textbook free-space half-wave dimensions ($L = \lambda_0/2$) and an improper airframe standoff ($h \approx \lambda_0/2$), because finite wire radius adds inductive self-reactance, mutual coupling shifts the active impedance away from $50\,\Omega$, and the carbon-fiber ground image cancels nadir radiation.
2. In 6-DoF flight, steering the phased array using world-frame angles without transforming through the drone's instantaneous roll-pitch-yaw rotation matrix mispoints both the GCS main lobe and the spatial jammer null whenever the aircraft banks.
3. Aggressive unregularized zero-forcing null steering excites anti-phase currents between coupled array elements, spiking the Total Active Reflection Coefficient (TARC), folding back power into the PA, and triggering thermal compression or shutdown.

Because the simulation engine (`/app/hfss_sim/`) couples Carter's Induced-EMF mutual impedance integrals, image theory, L-network transformation, 3D ZYX Euler kinematics, two-ray ground reflection over lossy soil, Doppler inter-carrier interference, and stateful PA thermal/queue/battery dynamics, no pre-trained lookup or textbook formula suffices without querying the physics engine and jointly optimizing the hardware and controller.

## Proposal screen (7 criteria)
1. **Verifiable (Strong Accept):** 100% deterministic analytical physics in NumPy/SciPy; zero LLM judges; verified in an isolated container (`environment_mode = "separate"`, `network_mode = "no-network"`).
2. **Well-specified (Accept):** Exact file paths (`/app/antenna_design.json`, `/app/hfss_characterization.json`, `/app/controller.py`, `/app/evaluation_summary.json`), schemas, physical units, and target operating bands are stated.
3. **Solvable (Strong Accept):** Solved via physical characterization of active array impedance + coordinate-descent/DE hardware design + body-frame active-TARC-regularized MVDR beamforming + feedback link control in <15 seconds of compute.
4. **Difficult for a good reason (Strong Accept):** Requires multi-domain reasoning across electromagnetics (mutual coupling, image theory, L-network matching, TARC), 3D rigid-body kinematics (world-to-body frame transformation), array signal processing (regularized MVDR null steering), and sequential constrained control (PA junction temperature, packet backlog, RF energy reserve).
5. **Grounded and interesting (Strong Accept):** Directly models the HFSS antenna-to-system workflow used in UAV RF link engineering.
6. **Scope (Strong Accept):** Electromagnetics, RF systems engineering, and reinforcement learning / sequential control.
7. **Outcome-verified (Strong Accept):** Verifier grades the physical performance of the submitted antenna design and closed-loop controller across both public and held-out 6-DoF flight scenarios.

Verdict: **Strong Accept**.

## Why it is hard
- **Active vs. isolated impedance:** Tuning the L-network to a single isolated dipole ($Z_{11}$) fails when all 4 elements radiate in phase because mutual impedances $Z_{12}, Z_{13}, Z_{14}$ and the airframe image elements shift the active feed impedance by $>35\,\Omega$.
- **Airframe image physics:** The conducting carbon-fiber belly acts as a reflector at distance $h$; naive $h = \lambda_0/2$ creates a broadside/nadir null via phase reversal on reflection.
- **Coupled TARC & MVDR nulling:** Unregularized null steering toward a jammer close to the GCS direction excites high difference-mode currents, driving $\text{TARC}(\mathbf{w}) > 0.7$, which collapses mismatch efficiency and heats the PA past its $85^\circ\text{C}$ compression knee.
- **3D Attitude rotation:** The array is fixed to the drone body frame; world-frame line-of-sight vectors must be rotated by $\mathbf{R}_{\text{world}\leftarrow\text{body}}(\text{roll}, \text{pitch}, \text{yaw})^T$ at every 100 ms step.
- **Stateful resource dynamics:** Transmit power and MCS selection must balance packet queue drain against Doppler ICI, PA junction temperature (cooled convectively by airspeed), and finite RF battery energy.

## Expected expert time and target solve rate
Expert hours: 2.5 - 4.0 hours   Target pass@k band for frontier models: 15% to 35%

## Contract (what the agent is told)
- Inspect `/app/hfss_sim/` (the read-only electromagnetic & 6-DoF channel simulator) and `/app/baseline/` (the failing legacy design and controller).
- Produce:
  1. `/app/antenna_design.json` — physical 2x2 array geometry and L-network parameters.
  2. `/app/hfss_characterization.json` — S-parameter sweep and active scan-impedance report computed from `hfss_sim` for the submitted design.
  3. `/app/controller.py` — `AdaptiveLinkController` implementing `reset(scenario_meta)` and `select_action(obs) -> dict`.
  4. `/app/evaluation_summary.json` — closed-loop evaluation summary across the 5 public scenarios.

## Acceptance (what proves done)
1. `/app/hfss_sim/` package files are unmodified.
2. `/app/antenna_design.json` satisfies physical geometry bounds and achieves target return loss, impedance bandwidth, realized gain, and active scan reflection performance when evaluated by the independent verifier's HFSS engine.
3. `/app/hfss_characterization.json` matches the independent HFSS engine recomputation for `/app/antenna_design.json`.
4. `/app/controller.py` runs closed-loop with `/app/antenna_design.json` across all 5 public flight missions and meets all link reliability, delivery ratio, thermal, energy, and return thresholds, matching `/app/evaluation_summary.json`.
5. `/app/controller.py` generalizes closed-loop with `/app/antenna_design.json` to 5 held-out adversarial 6-DoF flight missions in the verifier container without link loss, thermal overload, or energy exhaustion.

## Scope
Agent may create/modify `/app/antenna_design.json`, `/app/hfss_characterization.json`, `/app/controller.py`, `/app/evaluation_summary.json`, and any helper scripts under `/app/`. `/app/hfss_sim/` must not be modified.

## Validation
- `scripts/lint-task.sh task/Piyush`
- `harbor trials start --path task/Piyush --agent oracle` (x2 determinism)
- No-op, baseline, naive, alternative solution, semantic mutants (M1-M6), integrity/cheat mutants (I1-I4), per-instance null battery (Gate A).

	# Task brief: drone-hfss-link-codesign

	Status: APPROVED Grader version: v2.0 Owner: Piyush Date: 2026-10-25

	## Capability claim
	A pass proves that an agent can jointly solve a coupled electromagnetic structure design problem (3D array geometry, mutual-coupling active impedance, and L-section reactive matching network) and a sequential 6-DoF flight beamforming and link-control problem (body-frame attitude transformations, jammer nulling under active reflection constraints, and thermal/energy/queue management) from physical simulation telemetry. A fail does not distinguish between an electromagnetic mismatch failure and a flight-control failure without inspecting the per-test CTRF breakdown.

	## Seed
	Inspired by real UAV command-and-control (C2) and telemetry link failures during high-bank maneuvers in contested RF environments:
	1. A belly-mounted 2x2 planar dipole array on a conductive carbon-fiber quadrotor airframe exhibits severe scan blindness and high return loss when designed with textbook free-space half-wave dimensions ($L = \lambda_0/2$) and an improper airframe standoff ($h \approx \lambda_0/2$), because finite wire radius adds inductive self-reactance, mutual coupling shifts the active impedance away from $50\,\Omega$, and the carbon-fiber ground image cancels nadir radiation.
	2. In 6-DoF flight, steering the phased array using world-frame angles without transforming through the drone's instantaneous roll-pitch-yaw rotation matrix mispoints both the GCS main lobe and the spatial jammer null whenever the aircraft banks.
	3. Aggressive unregularized zero-forcing null steering excites anti-phase currents between coupled array elements, spiking the Total Active Reflection Coefficient (TARC), folding back power into the PA, and triggering thermal compression or shutdown.

	Because the simulation engine (`/app/hfss_sim/`) couples Carter's Induced-EMF mutual impedance integrals, image theory, L-network transformation, 3D ZYX Euler kinematics, two-ray ground reflection over lossy soil, Doppler inter-carrier interference, and stateful PA thermal/queue/battery dynamics, no pre-trained lookup or textbook formula suffices without querying the physics engine and jointly optimizing the hardware and controller.

	## Proposal screen (7 criteria)
	1. Verifiable (Strong Accept): 100% deterministic analytical physics in NumPy/SciPy; zero LLM judges; verified in an isolated container (`environment_mode = "separate"`, `network_mode = "no-network"`).
	2. Well-specified (Accept): Exact file paths (`/app/antenna_design.json`, `/app/hfss_characterization.json`, `/app/controller.py`, `/app/evaluation_summary.json`), schemas, physical units, and target operating bands are stated.
	3. Solvable (Strong Accept): Solved via physical characterization of active array impedance + coordinate-descent/DE hardware design + body-frame active-TARC-regularized MVDR beamforming + feedback link control in <15 seconds of compute.
	4. Difficult for a good reason (Strong Accept): Requires multi-domain reasoning across electromagnetics (mutual coupling, image theory, L-network matching, TARC), 3D rigid-body kinematics (world-to-body frame transformation), array signal processing (regularized MVDR null steering), and sequential constrained control (PA junction temperature, packet backlog, RF energy reserve).
	5. Grounded and interesting (Strong Accept): Directly models the HFSS antenna-to-system workflow used in UAV RF link engineering.
	6. Scope (Strong Accept): Electromagnetics, RF systems engineering, and reinforcement learning / sequential control.
	7. Outcome-verified (Strong Accept): Verifier grades the physical performance of the submitted antenna design and closed-loop controller across both public and held-out 6-DoF flight scenarios.

	Verdict: Strong Accept.

	## Why it is hard
	- Active vs. isolated impedance: Tuning the L-network to a single isolated dipole ($Z_{11}$) fails when all 4 elements radiate in phase because mutual impedances $Z_{12}, Z_{13}, Z_{14}$ and the airframe image elements shift the active feed impedance by $>35\,\Omega$.
	- Airframe image physics: The conducting carbon-fiber belly acts as a reflector at distance $h$; naive $h = \lambda_0/2$ creates a broadside/nadir null via phase reversal on reflection.
	- Coupled TARC & MVDR nulling: Unregularized null steering toward a jammer close to the GCS direction excites high difference-mode currents, driving $\text{TARC}(\mathbf{w}) > 0.7$, which collapses mismatch efficiency and heats the PA past its $85^\circ\text{C}$ compression knee.
	- 3D Attitude rotation: The array is fixed to the drone body frame; world-frame line-of-sight vectors must be rotated by $\mathbf{R}_{\text{world}\leftarrow\text{body}}(\text{roll}, \text{pitch}, \text{yaw})^T$ at every 100 ms step.
	- Stateful resource dynamics: Transmit power and MCS selection must balance packet queue drain against Doppler ICI, PA junction temperature (cooled convectively by airspeed), and finite RF battery energy.

	## Expected expert time and target solve rate
	Expert hours: 2.5 - 4.0 hours Target pass@k band for frontier models: 15% to 35%

	## Contract (what the agent is told)
	- Inspect `/app/hfss_sim/` (the read-only electromagnetic & 6-DoF channel simulator) and `/app/baseline/` (the failing legacy design and controller).
	- Produce:
	1. `/app/antenna_design.json` — physical 2x2 array geometry and L-network parameters.
	2. `/app/hfss_characterization.json` — S-parameter sweep and active scan-impedance report computed from `hfss_sim` for the submitted design.
	3. `/app/controller.py` — `AdaptiveLinkController` implementing `reset(scenario_meta)` and `select_action(obs) -> dict`.
	4. `/app/evaluation_summary.json` — closed-loop evaluation summary across the 5 public scenarios.

	## Acceptance (what proves done)
	1. `/app/hfss_sim/` package files are unmodified.
	2. `/app/antenna_design.json` satisfies physical geometry bounds and achieves target return loss, impedance bandwidth, realized gain, and active scan reflection performance when evaluated by the independent verifier's HFSS engine.
	3. `/app/hfss_characterization.json` matches the independent HFSS engine recomputation for `/app/antenna_design.json`.
	4. `/app/controller.py` runs closed-loop with `/app/antenna_design.json` across all 5 public flight missions and meets all link reliability, delivery ratio, thermal, energy, and return thresholds, matching `/app/evaluation_summary.json`.
	5. `/app/controller.py` generalizes closed-loop with `/app/antenna_design.json` to 5 held-out adversarial 6-DoF flight missions in the verifier container without link loss, thermal overload, or energy exhaustion.

	## Scope
	Agent may create/modify `/app/antenna_design.json`, `/app/hfss_characterization.json`, `/app/controller.py`, `/app/evaluation_summary.json`, and any helper scripts under `/app/`. `/app/hfss_sim/` must not be modified.

	## Validation
	- `scripts/lint-task.sh task/Piyush`
	- `harbor trials start --path task/Piyush --agent oracle` (x2 determinism)
	- No-op, baseline, naive, alternative solution, semantic mutants (M1-M6), integrity/cheat mutants (I1-I4), per-instance null battery (Gate A).