* `controllers/shepherd_dog/shepherd_dog.py`
- Tracks the first step at which each sheep crosses the gate; on
auto-finish (all sheep penned) prints a `[results]` summary
block: mode/drive/world/lidar/dogs/seed line, total simulated
time, per-sheep penning order with absolute step + seconds since
sim start, and the gate spread between the first and last
penning.
- Reads `HERDING_SEED` (env / runtime cfg) and seeds the
controller's RNG when set. Empty = time-based default = old
non-deterministic behaviour.
* `controllers/sheep/sheep.py` reads `HERDING_SEED` the same way
(loading `herding_runtime.cfg` itself so it works even when
Webots strips env vars) and seeds Python's RNG XOR'd with the
sheep's name hash, so a fixed seed gives a reproducible flock
trajectory without all sheep starting from identical wander state.
* `tools/run_webots.sh` writes `HERDING_SEED` into the runtime cfg
(empty when unset so existing scripts keep their stochastic
behaviour).
* `tools/webots_menu.sh` gains a Seed prompt (random / fixed
integer); the launch summary box shows the choice next to the
perception row.
* `Makefile`
- `make webots` now fires the interactive picker (replacing the
old positional invocation).
- `make webots_quick MODE=… DRIVE=… WORLD=… N=…` is the old
positional path, kept for batch / scripted use.
Smoke-tested: menu renders Mode → Drive → World → LiDAR → Dogs
→ Sheep → Perception → Seed → Headless prompts and shows the
selected Seed value in the launch summary. 126 pytest cases still
pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Single-command picker that prompts for every experimental knob the
project supports, then dispatches to `tools/run_webots.sh` with the
matching env vars. The banner reminds the user that the interpreter
path lives in `tools/setup_env.sh` (or `$HERDING_PYTHON`) so the
"this conda path won't exist on another machine" trap is hard to
fall into.
Prompts, in order:
Mode : bc | rl | strombom | sequential | universal
Drive : differential | mecanum
World : field | field_round
LiDAR FOV : 140° | 360° (skipped when drive=mecanum)
Dogs : 1 | 2 (axis-split — only ask leak if 2)
Sheep : 1..10
Perception : LiDAR | GT bypass
Headless : no (windowed) | yes (xvfb-run + fast mode)
Each prompt has a default marked with `*`; pressing Enter through the
whole flow runs the canonical demo (BC / diff / field / 140° /
1 dog / 5 sheep / LiDAR / windowed). The configuration is summarised
in a boxed block before the final "Launch? [Y/n]" confirm.
README quick-start now lists `tools/webots_menu.sh` as the
recommended starting point and shows the env-var-prefixed launcher
invocations (HERDING_LIDAR=360, HERDING_NDOGS=2, HERDING_USE_GT=1)
for non-interactive use.
126 pytest cases still pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Johnny Fernandes