d00da52c3c
Two small features.
(1) Portable interpreter
* `tools/setup_env.sh` exports HERDING_PYTHON (default points to the
project's conda env; override in your shell to retarget).
* Both `controllers/*/runtime.ini` files now use Webots' env-var
expansion: `COMMAND = $(HERDING_PYTHON)` so the Webots-launched
controllers pick up the same interpreter as the bash scripts.
* `tools/run_webots.sh`, `tools/webots_sweep{,_gt}.sh` and
`tools/calibrate_mecanum.sh` all source `setup_env.sh` at the top
instead of hard-coding `/home/jalf/miniconda3/envs/tir/bin`.
The hard-coded conda path is now exactly one line in `setup_env.sh`'s
fallback default — a single place to edit on a new machine, or
override-once via `export HERDING_PYTHON=...`.
(2) 360° LiDAR FOV ablation
* New `LIDAR_WEBOTS_360` preset matches the existing
`protos/ShepherdDog360.proto` (360 rays / 2π FOV / 15 m range).
* `tools/run_webots.sh` reads `HERDING_LIDAR=140|360` and swaps the
diff-drive proto accordingly (mecanum keeps 140° — the
ShepherdDogMecanum proto has its own LiDAR section). The variant
is written into `herding_runtime.cfg` so the controller can read
it even when Webots strips env vars.
* `controllers/shepherd_dog/shepherd_dog.py` picks the matching
`lidar_cfg` (`HERDING_WEBOTS.lidar` for 140°, `LIDAR_WEBOTS_360`
otherwise) and feeds it to `detections_from_scan` so the
perception pipeline interprets ray angles + max range correctly.
Smoke test: `HERDING_LIDAR=360 tools/run_webots.sh 5 strombom
differential field` launches with `ShepherdDog360.proto`, the
controller logs the new mode/drive/world line, and the dog is
penning sheep through 360° perception (4/5 at step 19200 before I
killed the test). No retraining required because the gym already
trains under `LIDAR_FULL` (360° preset).
126 pytest cases still pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
226 lines
7.9 KiB
Bash
Executable File
226 lines
7.9 KiB
Bash
Executable File
#!/bin/bash
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# Launch Webots with N sheep enabled and the chosen controller mode.
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# Generates a temporary world file in worlds/field_test.wbt with sheep
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# beyond N commented out, sets the env vars the dog controller reads,
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# then execs Webots on it.
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#
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# Usage:
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# tools/run_webots.sh [N] [MODE] [DRIVE] [WORLD]
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# N : number of active sheep (1..10), default 10
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# MODE : "bc" | "rl" | "strombom" | "sequential", default "bc"
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# DRIVE : "differential" | "mecanum", default "differential"
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# WORLD : base world name (without .wbt), default "field"
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# Supported: "field" (rectangular), "field_round" (circular)
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#
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# Examples:
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# tools/run_webots.sh 10 bc # behaviour-cloned MLP, diff drive
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# tools/run_webots.sh 10 rl mecanum # KL-PPO fine-tune, mecanum wheels
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# tools/run_webots.sh 5 sequential field_round # analytic baseline, round field
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# tools/run_webots.sh 3 strombom mecanum field_round # Strömbom, mecanum, round
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#
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# Notes:
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# * bc loads training/runs/bc/policy.zip, rl loads training/runs/rl.
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# Override via HERDING_POLICY_DIR=/path/to/run env var.
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# * Conda env "tir" must be active (provides stable-baselines3 + torch).
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#
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# Headless-ish (no 3D view, fast sim, no modal dialogs):
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# WEBOTS_HEADLESS=1 make webots N=10 MODE=rl DRIVE=mecanum
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# WEBOTS_HEADLESS=1 tools/run_webots.sh 10 rl mecanum
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# This passes --no-rendering --minimize --mode=fast --batch to webots.
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# Webots still needs a display (Qt); on a machine without one use e.g.:
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# xvfb-run -a env WEBOTS_HEADLESS=1 tools/run_webots.sh 10 rl mecanum
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# Optional extra CLI tokens (space-separated):
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# WEBOTS_EXTRA_ARGS="--stdout --stderr" WEBOTS_HEADLESS=1 tools/run_webots.sh 10 rl
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set -e
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# Make sure HERDING_PYTHON is resolved and on PATH so Webots inherits
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# the right interpreter (controllers/{shepherd_dog,sheep}/runtime.ini
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# both read $HERDING_PYTHON via env-var expansion).
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source "$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )/setup_env.sh"
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N=${1:-10}
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MODE=${2:-bc}
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DRIVE=${3:-differential}
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WORLD=${4:-field}
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if (( N < 0 || N > 10 )); then
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echo "N must be 0..10, got $N" >&2; exit 1
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fi
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case "$MODE" in
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bc|rl|strombom|sequential|universal|calibrate) ;;
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*) echo "MODE must be bc|rl|strombom|sequential|universal|calibrate, got '$MODE'" >&2; exit 1 ;;
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esac
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case "$DRIVE" in
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differential|mecanum) ;;
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*) echo "DRIVE must be differential|mecanum, got '$DRIVE'" >&2; exit 1 ;;
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esac
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ROOT="$( cd "$( dirname "${BASH_SOURCE[0]}" )/.." && pwd )"
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SRC="$ROOT/worlds/${WORLD}.wbt"
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if [[ ! -f "$SRC" ]]; then
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echo "World file not found: $SRC" >&2; exit 1
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fi
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DST="$ROOT/worlds/${WORLD}_test.wbt"
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if [[ -n "${HERDING_POLICY_DIR:-}" ]]; then
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RESOLVED_POLICY_DIR="$HERDING_POLICY_DIR"
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else
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# The training pipeline writes policies to:
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# training/runs/{bc,rl}_<drive>_<world>
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# Try that first; fall back to the drive-only and finally the
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# bare-mode legacy paths so older policy checkouts still load.
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if [[ "$MODE" == "rl" ]]; then
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BASE="rl"
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else
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BASE="bc"
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fi
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for CAND in \
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"$ROOT/training/runs/${BASE}_${DRIVE}_${WORLD}" \
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"$ROOT/training/runs/${BASE}_${DRIVE}" \
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"$ROOT/training/runs/${BASE}"
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do
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if [[ -d "$CAND" ]]; then
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RESOLVED_POLICY_DIR="$CAND"
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break
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fi
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done
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: "${RESOLVED_POLICY_DIR:=$ROOT/training/runs/${BASE}_${DRIVE}_${WORLD}}"
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fi
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cp "$SRC" "$DST"
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# LiDAR FOV variant: HERDING_LIDAR=140 (default) or 360 (ablation).
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# 360° is only supported for differential drive; the mecanum proto
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# always uses the 140° sensor matching ShepherdDog.proto.
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LIDAR_VARIANT="${HERDING_LIDAR:-140}"
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if [[ "$LIDAR_VARIANT" != "140" && "$LIDAR_VARIANT" != "360" ]]; then
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echo "HERDING_LIDAR must be 140 or 360, got '$LIDAR_VARIANT'" >&2; exit 1
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fi
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if [[ "$LIDAR_VARIANT" == "360" && "$DRIVE" == "mecanum" ]]; then
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echo "[run_webots] HERDING_LIDAR=360 not available for mecanum drive — falling back to 140." >&2
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LIDAR_VARIANT="140"
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fi
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export HERDING_LIDAR="$LIDAR_VARIANT"
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# Swap robot proto based on drive mode + LiDAR variant.
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# Base worlds reference ShepherdDog (diff-drive 140°). For mecanum we
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# swap in ShepherdDogMecanum; for the 360° ablation we swap in
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# ShepherdDog360.
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if [[ "$DRIVE" == "mecanum" ]]; then
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sed -i 's|"../protos/ShepherdDog.proto"|"../protos/ShepherdDogMecanum.proto"|' "$DST"
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sed -i 's|^ShepherdDog {|ShepherdDogMecanum {|' "$DST"
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elif [[ "$LIDAR_VARIANT" == "360" ]]; then
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sed -i 's|"../protos/ShepherdDog.proto"|"../protos/ShepherdDog360.proto"|' "$DST"
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sed -i 's|^ShepherdDog {|ShepherdDog360 {|' "$DST"
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fi
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if [[ "$DRIVE" == "mecanum" ]]; then
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# Inject mecanum roller contact properties. The proto's rollers are
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# split into two contact materials so that we can keep the friction
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# axes oriented along each roller's free-spin direction — but with
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# physical roller hinges (no longer plain cylinder wheels) the
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# ground contact is via the capsules and standard friction works.
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# Slightly bumped coulombFriction keeps the rollers gripping during
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# mecanum strafing.
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python3 -c "
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with open('$DST', 'r') as f:
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txt = f.read()
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mec = ''' ContactProperties {
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material1 \"MecanumWheelA\"
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coulombFriction [
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2.0
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]
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bounce 0
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forceDependentSlip [
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0.005
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]
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softCFM 0.0001
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}
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ContactProperties {
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material1 \"MecanumWheelB\"
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coulombFriction [
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2.0
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]
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bounce 0
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forceDependentSlip [
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0.005
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]
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softCFM 0.0001
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}
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'''
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# The contactProperties array closes with ' ]\n}' (2-space indent ] then WorldInfo }).
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# Insert the new block just before that closing ].
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txt = txt.replace('\n ]\n}', '\n' + mec + ' ]\n}', 1)
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with open('$DST', 'w') as f:
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f.write(txt)
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"
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fi
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# Comment out sheep N+1..10 by prefixing the matching Sheep { ... } line.
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for i in $(seq $((N+1)) 10); do
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sed -i "s|^Sheep .* \"sheep${i}\".*|# &|" "$DST"
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done
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active=$(grep -c '^Sheep' "$DST" || true)
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echo "------------------------------------------------------------"
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echo "World : $DST"
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echo "Mode : $MODE"
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echo "Drive : $DRIVE"
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echo "Sheep : $active active"
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echo "Policy dir : $RESOLVED_POLICY_DIR"
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echo "------------------------------------------------------------"
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# Webots strips HERDING_* env vars from controller subprocesses in some
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# setups, so we also write a runtime config file the controller reads.
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cat > "$ROOT/herding_runtime.cfg" <<EOF
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HERDING_MODE=$MODE
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HERDING_POLICY_DIR=$RESOLVED_POLICY_DIR
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HERDING_DRIVE=$DRIVE
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HERDING_WORLD=$WORLD
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HERDING_LIDAR=$LIDAR_VARIANT
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HERDING_USE_GT=${HERDING_USE_GT:-0}
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EOF
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export HERDING_MODE="$MODE"
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export HERDING_POLICY_DIR="$RESOLVED_POLICY_DIR"
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export HERDING_DRIVE="$DRIVE"
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export HERDING_WORLD="$WORLD"
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export HERDING_LIDAR="$LIDAR_VARIANT"
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# The controller writes this sentinel when all GT sheep are penned. We
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# poll for it and kill Webots so the run finishes cleanly instead of
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# idling for minutes after the task is done.
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DONE_FILE="$ROOT/training/.run_done"
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mkdir -p "$(dirname "$DONE_FILE")"
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rm -f "$DONE_FILE"
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if [[ "${WEBOTS_HEADLESS:-}" == "1" ]]; then
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echo "[run_webots] headless flags: --no-rendering --minimize --mode=fast --batch"
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# shellcheck disable=SC2086
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webots --no-rendering --minimize --mode=fast --batch ${WEBOTS_EXTRA_ARGS:-} "$DST" &
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else
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# shellcheck disable=SC2086
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webots ${WEBOTS_EXTRA_ARGS:-} "$DST" &
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fi
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WEBOTS_PID=$!
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cleanup() {
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kill "$WEBOTS_PID" 2>/dev/null || true
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wait "$WEBOTS_PID" 2>/dev/null || true
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exit 0
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}
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trap cleanup INT TERM
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# Poll for the sentinel; bail when Webots exits on its own or when the
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# user closes the window.
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while kill -0 "$WEBOTS_PID" 2>/dev/null; do
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if [[ -f "$DONE_FILE" ]]; then
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echo "[run_webots] all sheep penned — closing Webots"
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sleep 1 # let the controller print its line
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kill "$WEBOTS_PID" 2>/dev/null || true
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break
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fi
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sleep 1
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done
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wait "$WEBOTS_PID" 2>/dev/null || true
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