What it is
An autonomous quadrotor flies a five-station obstacle course in MuJoCo using only its onboard camera. Classical CV and control stay in code; a small Jev model decides what each situation means. For robotics researchers exploring judgment models in live control loops.
How it uses Jev
At ~2.5 Hz, on a symbolic scene of five range sectors, blocker height, top-edge visibility, and target position, Jev answers three questions in one call: maneuver (Choice: hold_course/gap_left/gap_right/climb/brake/reacquire), risk (Score), and target_truly_lost (Noul). Code decides when to ask; a 50 Hz reflex layer can override any judgment. Jev is advisory only.
Primitives:choicescorenoul
Technique worth stealing
Include the variable the answer depends on in the state: adding obstruction top-edge height and climb ceiling moved 'climb' from never-chosen to p=0.93.
Try it
./setup.sh, cp .env.example .env with your key, then .venv/bin/python run.py --seconds 65 --seeds 1
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricyes0.78
- Shows a System One patternyes0.81
- Handles uncertaintyno0.08
- Measuredno0.17
- Runnableno0.27
- Worth recommendingunclear0.51
- Model replicano0.05
- Problem scopescore on a 0–2 scale0.12
- About Jevyes0.98
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.