File size: 8,224 Bytes
0c3dd1d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | # Episode output schema (tr-c1-episode/1)
Each completed episode is a directory `OUT/episodes/<episode_id>/` that appears
atomically (written as `.tmp_<id>_<pid>` and renamed). Infrastructure
failures go to `OUT/infrastructure_errors/<episode_id>_<ms>/` instead and are
retried by the next `campaign.py` invocation. Files:
| File | Content |
| --- | --- |
| `episode_config.json` | normalized config (defaults filled); its SHA256 over canonical JSON is `config_hash` |
| `ticks.csv.gz` | one row per 10 Hz controller tick |
| `state100.csv.gz` | 100 Hz true-state log (every 10 physics steps, from step 0) |
| `summary.json` | outcome, metrics, wall-time split, file hashes |
| `server_stderr.txt` | physics-server stderr |
| `mpc_diag.csv.gz` | only for the released MPC and MPC-based plug-ins: one row per OSQP solve, see below |
| `obs_noise.csv.gz` | only when observation noise is on: one row per tick that observed a state |
CSV: gzip (mtime 0, deterministic bytes), header row, floats written with
Python `repr` (exact round trip), empty field = not applicable. Units: m, rad,
s, m/s. Angles CCW positive; yaw from the released formula
`atan2(2(e0 e3 + e1 e2), e0^2 + e1^2 - e2^2 - e3^2)` on the Chrono chassis
quaternion (e0 = w). Position = chassis COG (what ChROSBodyHandler publishes).
## ticks.csv.gz
| Column | Meaning |
| --- | --- |
| tick, step, t, t_ctrl | tick index; physics boundary (steps completed); ChSystem time; t - control_start_s |
| status | `ok`, `no_state` (released pub_callback returned before the first pose, ros_emulated start-up), `controller_dead` (after a controller failure), `controller_solver_failure`, `controller_exception`, `controller_nonfinite_output` |
| obs_pub_step, obs_age_steps | boundary of the state the controller saw (ideal: = step) and its age |
| x y z yaw yaw_unwrapped speed vx vy yaw_rate | TRUE chassis state at the tick boundary (yaw_unwrapped over ticks; speed = planar norm of COG velocity; yaw_rate = world-z angular rate) |
| obs_x obs_y obs_theta obs_v | what the released node stored (state_callback/vel_callback; includes observation noise) - these are the released logger's x, y, theta |
| e0..e3 | controller input `error_state(1.0)` (1 m lookahead) captured from pub_callback |
| et0..et3 | `error_state(0.0)` (= released `e_tracking`): et1 lateral, et2 heading error |
| idx_lookahead, idx_track, arc_s_track | nearest-waypoint indices of the two error states; arc length of idx_track |
| raw_throttle, raw_steering | controller law output before the rate limit (MPC steering already x1.6667) |
| rl_steering, rate_limited | `self.steering` after the 0.25/tick limiter; whether the limiter acted |
| published, pub_steering, pub_throttle, pub_braking | published DriverInputs (clipped) |
| apply_step, applied_* | boundary at which THIS tick's command reached `driver->Set*` and the stored driver values (after steering bias, ChDriver clamp); -1 = superseded before any driver tick (ros_emulated) or never applied |
| drv_steering, drv_throttle, drv_braking | driver inputs in effect at the tick boundary (before this tick's command) |
| compute_wall_s | wall time of pub_callback (excluded from determinism comparisons) |
## state100.csv.gz
`step, t, x, y, z, yaw, yaw_unwrapped, speed, vx, vy, yaw_rate` (true state),
`in_steering, in_throttle, in_braking` (inputs used by the last physics step),
`e_long, e_lat, e_head, e_speed, nearest_idx, arc_s` (released
`error_state(0.0)` definitions evaluated on the true state, vectorised and
checked against the released function), `progress_idx` (path_completion
tracker), `dist_min` (distance to nearest waypoint, divergence rule).
## summary.json (selected keys)
- `status`: `ok` | `infrastructure_error`. `outcome` (only when ok):
`horizon_reached`, `completed`, `timeout`, `diverged`,
`controller_solver_failure`, `controller_exception`,
`controller_nonfinite_output`.
- `failure`: category, tick, step, t, traceback (controller failures and
infrastructure errors).
- `tube_entry_time_100hz_s`: first 100 Hz sample (t relative to control start)
with |e_lat| < tube_lat_m and |e_head| < tube_head_rad (true state);
`tube_entry_time_tick_s`: same on published ticks (et1, et2);
`stay_in_tube_time_100hz_s`, `fraction_inside_tube_after_entry`,
`tube_exits_after_entry`; `max_abs_lat_100hz_m`, `final_e_*`.
- `completion_step` (path_completion), `run_mae_lateral_m`,
`run_mae_heading_rad`, `run_mae_samples`: definitions of physical/physical_runs.py on
published ticks' observed pose up to completion (or the last tick).
- `wall`: `init_s` (controller reset + server spawn/initialisation),
`stepping_s` (physics round trips), `controller_s` (sum of pub_callback),
`other_s`, `total_s`; `physics_pure_step_wall_s` (inside the server);
`server_spawn_to_ready_s`.
- `files`: SHA256 of the two CSV files; `config_hash`; `reference_sha256`; `mpc_osqp_adaptive_rho_interval` used.
## mpc_diag.csv.gz (READ-ONLY OSQP diagnostics)
One row per `osqp.OSQP.solve()` made during a controller tick (released MPC, `plugin:wrapped_released` with base
mpc, `plugin:mpc_n5`). Recorded by a wrapper around `osqp.OSQP.solve` that returns the solver's results object
unchanged; commands are bitwise identical with and without it.
| Column | Meaning |
| --- | --- |
| tick, step, solve_index | controller tick, its boundary, index of the solve within the tick (always 0 for nsim = 1) |
| status, status_val, status_polish | OSQP `res.info` status text / code / polish status (`solved` = 1) |
| iter, rho_updates, rho_estimate | ADMM iterations, number of rho updates, final rho estimate |
| obj_val, pri_res, dua_res | objective, primal and dual residuals |
| setup_time, solve_time, update_time, polish_time, run_time | OSQP's own WALL-CLOCK timings in s (excluded from determinism comparisons) |
| adaptive_rho_interval_requested | value passed to `setup` (25 = the runner pin; empty = OSQP automatic, chosen from wall-clock time inside the solver and not readable safely through the osqp 0.6.5 Python API) |
| setup_max_iter, setup_warm_start | values the released code passed to `setup` (10000, true) |
| qp_n, qp_m | QP size from `OSQP.dimensions()` (N = 10: 64 x 108; N = 5: 34 x 58) |
| diag_error | empty unless reading the diagnostics failed (never changes an outcome) |
Summary key `mpc_osqp`: n_solves, status_counts, n_not_solved, iter_total / mean / max, rho_updates_total,
n_solves_with_rho_update, rho_estimate_min / max, adaptive_rho_interval_requested, qp_dims, n_diag_errors (all
deterministic); `wall.osqp_run_s` = sum of run_time.
## obs_noise.csv.gz
`tick, step, obs_pub_step, z_x, z_y, z_yaw, noise_x, noise_y, noise_yaw`: the standard normals of the observed
publication (`SeedSequence([7301, obs_noise.seed, obs_pub_step])`) and the noise actually added (std x z; exactly 0
where std = 0). Summary key `obs_noise_model` names the model (null without noise).
## Recovery summary fields
`horizon_mean_abs_e_lat_m`, `horizon_mean_abs_e_head_rad` (100 Hz true-state tracking error, every sample from
control start t = 0 to the end of the log), `horizon_mean_n_samples`, `horizon_mean_from_sim0_*` (from sim time 0),
`horizon_mean_covers_horizon`; `by_H` = {"15", "25", "40"} (windows 0 <= t <= H inside the horizon): abs_e_lat_m,
abs_e_head_rad, n_samples, covered, tube_entry_s, tube_exits_after_entry; `divergence_events` (offline replay of the
online rule: start_step, fire_step, end_step), `n_divergence_events`, `divergence_flag`, `diverged_then_recovered`,
`first_tube_entry_after_divergence_s`, `entered_then_diverged`, `returned_within_divergence_dist`,
`divergence_offline_matches_online`; `controller_params_effective` (plug-ins: parameters with defaults filled in).
With `termination.stop_on_divergence = false` the episode always runs to `horizon_s`; the online outcome is
still `diverged` once the rule fires. The post-entry exit count is `tube_exits_after_entry`.
## Run level
`OUT/summary.jsonl` (append-only, one flattened row per finished episode per
invocation), `OUT/summary.csv` (rebuilt from all `summary.json`, sorted by
episode_id), `OUT/manifest_<run_id>.json` (input hashes, environment,
config hashes, counts, per-episode wall times).
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