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Agentic co-design of low-cost robots

Does tilting a quadrotor's rotors buy the yaw authority that no attitude controller could?

research/codesign-aero-cant

Does a rotor cant angle, co-designed with arm length and propeller size, beat the yaw limit that control-law changes could not move? In simulation yes: joint co-design with free cant (chosen at the 35° bound in 5 of 5 seeds) cuts held-out attitude error from 15.22° to 12.32°, at equal evaluations.

8 tests

What it found

Follow-up to codesign-aero-coupled, which found yaw (reaction-torque limited) dominates quadrotor attitude error and that no control law changed that. Here the rotor cant angle α is a design variable: tilting rotors about their arms, alternating with spin direction, raises yaw authority to 2ΔT(κ cosα + r sinα) but costs thrust (every rotor is sized for T/cosα: more mass, more cost). With the PID retuned at each angle (6 airframes × 5 seeds, 64 held-out episodes), error falls from 17.77° at α = 0 to 15.38° at 35° (paired: better in 20 of 20 feasible pairs, mean −2.85°); the gain survives a 0.5× and 3× reaction-torque ratio. Joint CMA-ES co-design of arm length, propeller size, cant and gains (1920 evaluations, 5 seeds) reaches 12.32° against 15.22° with cant fixed at 0, and picks 34–35°, the edge of the allowed range, every time, so the optimum is not located. Higher cant also makes some airframes infeasible under the cost cap (20 of 30 grid cells feasible at 30–35°). Limits: the reaction-torque ratio, plant ranges and cost model are assumed and swept, not measured; tilt-induced efficiency loss, internal force fighting and roll/pitch cross-coupling from the tilted thrust vectors are not modelled; attitude only, step references.

A figure from its own output

Figure produced by research/codesign-aero-cant: cant
codesign-aero-cant/experiments/cant.png, written by the project's own experiment code.

Paper, code and results

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Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.