Files
lerobot/tests/navigation/test_agent.py
T
Pepijn e6616456fb navigation: port value maps, features, skills, agent + dog-nav CLI
Copied from the dyna360 research stack into lerobot.navigation:

- value_map.py: DynaMem §3.4 exploration scoring (V_T recency + V_S
  query-similarity, combined value with distance discount).
- features.py: SiglipFeatureExtractor (MaskCLIP dense patches, lazy
  transformers) + FeatureExtractor protocol + BasisVectorFeatureExtractor
  stand-in for model-free dry-run/tests.
- skills.py: SpatialSkills locate/goto/explore over the voxel memory +
  base controller + text encoder.
- agent.py: DeterministicAgent (locate→goto / explore→relocate policy) +
  HardcodedTaskParser (regex NL→Task).
- sim.py: self-contained synthetic scenes (kitchen) + basis-vector text
  encoder, replacing the dyna360 eval harness for dry-run.
- dog_cli.py: `dog-nav` interactive REPL — idle→explore, prompt→locate+
  goto (explore-to-find on miss), preemptible, Ctrl-C e-stop, --dry-run.

Silenced benign fp16 matmul warnings in query/similarity via np.errstate.
Pure numpy + optional lazy torch/transformers; 67 new tests (116 total in
tests/navigation/), all model/hardware-free. Deliverable runs:
`python -m lerobot.navigation.dog_cli --dry-run`.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-20 18:27:07 +02:00

249 lines
8.6 KiB
Python

#!/usr/bin/env python
# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Unit tests for the C1 deterministic agent + language parser."""
from __future__ import annotations
from dataclasses import dataclass, field
import numpy as np
from lerobot.navigation.agent import (
AgentConfig,
DeterministicAgent,
HardcodedTaskParser,
Task,
)
from lerobot.navigation.skills import ExploreResult, GotoResult, LocateResult
# ----- fakes -------------------------------------------------------------
@dataclass
class FakeSkills:
"""Programmable :class:`SpatialSkills` stand-in. Each method consults a
pre-recorded script and bumps a call counter so tests can assert the
deterministic policy made the right sequence of calls."""
locate_script: list[LocateResult] = field(default_factory=list)
explore_script: list[ExploreResult] = field(default_factory=list)
goto_script: list[GotoResult] = field(default_factory=list)
locate_calls: list[str] = field(default_factory=list)
goto_calls: list[tuple[float, float, float]] = field(default_factory=list)
explore_calls: list[str | None] = field(default_factory=list)
def locate(self, text: str) -> LocateResult:
self.locate_calls.append(text)
if not self.locate_script:
return LocateResult(False, None, -1.0, 0, text)
return self.locate_script.pop(0)
def explore(self, query: str | None = None) -> ExploreResult:
self.explore_calls.append(query)
if not self.explore_script:
return ExploreResult(None, False, 0.0, "no frontier")
return self.explore_script.pop(0)
def goto(self, xyz: tuple[float, float, float], **_: object) -> GotoResult:
self.goto_calls.append(xyz)
if not self.goto_script:
return GotoResult(True, xyz, 0.0, 0, "ok", [])
return self.goto_script.pop(0)
@property
def base(self):
# Minimal stub: agent's teleport branch isn't exercised by these tests.
class _Base:
def move(self, *a, **k):
pass
def pose(self):
return np.eye(4)
return _Base()
# ----- HardcodedTaskParser ------------------------------------------------
def test_parser_simple_go_to():
t = HardcodedTaskParser().parse("go to the mug")
assert t.targets == ["mug"]
def test_parser_strips_punctuation_and_articles():
t = HardcodedTaskParser().parse("Find the red lamp.")
assert t.targets == ["red lamp"]
def test_parser_multi_step():
t = HardcodedTaskParser().parse("go to the mug then the chair")
assert t.targets == ["mug", "chair"]
def test_parser_no_verb_treats_command_as_target():
"""``parser.parse('couch')`` should still produce a usable Task."""
t = HardcodedTaskParser().parse("couch")
assert t.targets == ["couch"]
def test_parser_empty_string_returns_empty_task():
t = HardcodedTaskParser().parse(" ")
assert t.targets == []
def test_parser_split_by_comma():
t = HardcodedTaskParser().parse("go to mug, chair")
assert t.targets == ["mug", "chair"]
# ----- DeterministicAgent policy -----------------------------------------
def _ok_locate(xyz=(1.0, 0.0, 1.0), conf=0.9) -> LocateResult:
return LocateResult(True, xyz, conf, 10, "x")
def _miss_locate(conf=0.05) -> LocateResult:
return LocateResult(False, None, conf, 0, "x")
def _ok_goto(xyz=(1.0, 0.0, 1.0)) -> GotoResult:
return GotoResult(True, xyz, 0.0, 5, "ok", [])
def _failed_goto(xyz=(1.0, 0.0, 1.0)) -> GotoResult:
return GotoResult(False, (0.0, 0.0, 0.0), 1.4, 0, "no path", [])
def _explore_to(xyz=(2.0, 0.0, 2.0)) -> ExploreResult:
return ExploreResult(xyz, True, 2.8, "ok")
def test_agent_hit_then_goto():
"""Found on first call → no explore, single goto."""
skills = FakeSkills(
locate_script=[_ok_locate()],
goto_script=[_ok_goto()],
)
agent = DeterministicAgent(skills, AgentConfig(max_explore_iters=3))
res = agent.execute(Task(targets=["mug"]))
assert res.fully_successful
assert skills.locate_calls == ["mug"]
assert skills.goto_calls == [(1.0, 0.0, 1.0)]
assert skills.explore_calls == []
assert res.target_results[0].n_explore_iters == 0
def test_agent_explore_then_relocate_then_goto():
"""First locate misses → explore → goto-to-frontier → re-locate finds → final goto."""
skills = FakeSkills(
locate_script=[_miss_locate(), _ok_locate()],
explore_script=[_explore_to((3.0, 0.0, 0.0))],
goto_script=[_ok_goto((3.0, 0.0, 0.0)), _ok_goto((1.0, 0.0, 1.0))],
)
agent = DeterministicAgent(skills, AgentConfig(max_explore_iters=3))
res = agent.execute(Task(targets=["mug"]))
assert res.fully_successful
assert skills.locate_calls == ["mug", "mug"]
assert skills.explore_calls == ["mug"]
assert skills.goto_calls == [(3.0, 0.0, 0.0), (1.0, 0.0, 1.0)]
assert res.target_results[0].n_explore_iters == 1
def test_agent_budget_exhaustion():
"""All N+1 locate calls miss → return budget_exhausted."""
skills = FakeSkills(
locate_script=[_miss_locate() for _ in range(5)],
explore_script=[_explore_to() for _ in range(4)],
goto_script=[_ok_goto((2.0, 0.0, 2.0)) for _ in range(4)],
)
agent = DeterministicAgent(skills, AgentConfig(max_explore_iters=3))
res = agent.execute(Task(targets=["mug"]))
assert res.fully_successful is False
r = res.target_results[0]
assert r.reason == "budget_exhausted"
assert r.n_explore_iters == 3
# 4 locate calls: initial + 3 retries.
assert len(skills.locate_calls) == 4
assert len(skills.explore_calls) == 3
def test_agent_no_frontier_short_circuits():
"""If explore can't find a frontier, give up immediately — no point looping."""
skills = FakeSkills(
locate_script=[_miss_locate()],
explore_script=[ExploreResult(None, False, 0.0, "no frontier")],
)
agent = DeterministicAgent(skills, AgentConfig(max_explore_iters=3))
res = agent.execute(Task(targets=["mug"]))
r = res.target_results[0]
assert r.reached is False
assert r.reason == "no_frontier"
assert len(skills.locate_calls) == 1
assert len(skills.explore_calls) == 1
def test_agent_failed_goto_does_not_loop_back():
"""If locate finds the target but goto fails (e.g. no path), report the
failure cleanly rather than retrying."""
skills = FakeSkills(
locate_script=[_ok_locate()],
goto_script=[_failed_goto()],
)
agent = DeterministicAgent(skills)
res = agent.execute(Task(targets=["mug"]))
r = res.target_results[0]
assert r.reached is False
assert r.reason == "no path"
def test_agent_multi_target_bails_on_first_failure():
"""The spec says sequential targets stop at the first failure so the
caller sees the failure clearly."""
skills = FakeSkills(
locate_script=[_miss_locate()],
explore_script=[ExploreResult(None, False, 0.0, "no frontier")],
)
agent = DeterministicAgent(skills, AgentConfig(max_explore_iters=0))
res = agent.execute(Task(targets=["mug", "chair"]))
assert len(res.target_results) == 1 # bailed before chair
assert res.target_results[0].target == "mug"
def test_agent_swap_parser_does_not_change_policy():
"""Acceptance from the spec: 'swapping Qwen for a hardcoded target string
yields the same spatial behaviour'. Same skills script, same scripted
locate/goto, regardless of how the command was parsed."""
parser = HardcodedTaskParser()
for command in ("mug", "go to the mug", "find the mug"):
skills = FakeSkills(locate_script=[_ok_locate()], goto_script=[_ok_goto()])
agent = DeterministicAgent(skills)
res = agent.execute_command(command, parser)
assert res.fully_successful
assert skills.goto_calls == [(1.0, 0.0, 1.0)]
def test_agent_empty_command_reports_parse_failure():
skills = FakeSkills()
agent = DeterministicAgent(skills)
res = agent.execute_command("", HardcodedTaskParser())
assert res.fully_successful is False
assert res.target_results[0].reason == "parse_empty"
assert skills.locate_calls == []