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Original file line number Diff line number Diff line change
@@ -0,0 +1,180 @@
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

"""
Tests for controller pose validity handling in the Se3 retargeters.

A connected controller can report an invalid grip pose (e.g. resting on a
table with pose tracking lost): the ControllerInput group is present (not
``is_none``) but ``grip_is_valid`` is False and the orientation is a
zero-norm quaternion. Regression: Se3AbsRetargeter/Se3RelRetargeter used to
feed that quaternion to ``Rotation.from_quat``, raising
``ValueError: Found zero norm quaternions in `quat`.`` and killing the
retargeting pipeline.
"""

import numpy as np
import numpy.testing as npt
import pytest

from isaacteleop.retargeting_engine.interface import (
ComputeContext,
ExecutionEvents,
ExecutionState,
OptionalTensorGroup,
TensorGroup,
)
from isaacteleop.retargeting_engine.interface.retargeter_core_types import GraphTime
from isaacteleop.retargeting_engine.interface.tensor_group_type import (
OptionalTensorGroupType,
)
from isaacteleop.retargeting_engine.tensor_types import ControllerInputIndex

from isaacteleop.retargeters import (
Se3AbsRetargeter,
Se3RelRetargeter,
Se3RetargeterConfig,
)

_DEVICE = "controller_right"


def _make_context() -> ComputeContext:
return ComputeContext(
graph_time=GraphTime(sim_time_ns=0, real_time_ns=0),
execution_events=ExecutionEvents(
reset=False, execution_state=ExecutionState.RUNNING
),
)


def _build_io(retargeter):
"""Build inputs/outputs for a retargeter, using OptionalTensorGroup for optional specs."""
inputs = {}
for k, v in retargeter.input_spec().items():
if isinstance(v, OptionalTensorGroupType):
inputs[k] = OptionalTensorGroup(v)
else:
inputs[k] = TensorGroup(v)
outputs = {}
for k, v in retargeter.output_spec().items():
if isinstance(v, OptionalTensorGroupType):
outputs[k] = OptionalTensorGroup(v)
else:
outputs[k] = TensorGroup(v)
return inputs, outputs


def _fill_controller(group, *, grip_valid: bool, position=(0.0, 0.0, 0.0)) -> None:
"""Populate a present ControllerInput group.

When *grip_valid* is False the orientation is the zero-norm quaternion a
real ControllersSource emits for a connected controller whose pose
tracking is lost.
"""
orientation = (
np.array([0.0, 0.0, 0.0, 1.0], dtype=np.float32)
if grip_valid
else np.zeros(4, dtype=np.float32)
)
group[ControllerInputIndex.GRIP_POSITION] = np.asarray(position, dtype=np.float32)
group[ControllerInputIndex.GRIP_ORIENTATION] = orientation
group[ControllerInputIndex.GRIP_IS_VALID] = grip_valid


class TestSe3AbsRetargeterPoseValidity:
@pytest.fixture()
def retargeter(self):
cfg = Se3RetargeterConfig(input_device=_DEVICE)
return Se3AbsRetargeter(cfg, name="se3abs")

def test_invalid_grip_holds_last_pose(self, retargeter):
"""Present-but-invalid grip must not raise and must hold the last pose."""
inputs, outputs = _build_io(retargeter)
stale = np.array([1.0, 2.0, 3.0, 0.5, 0.5, 0.5, 0.5], dtype=np.float32)
retargeter._last_pose = stale.copy()

_fill_controller(inputs[_DEVICE], grip_valid=False)
retargeter.compute(inputs, outputs, _make_context())

pose = np.from_dlpack(outputs["ee_pose"][0])
npt.assert_array_almost_equal(pose, stale)

def test_valid_grip_after_invalid_resumes(self, retargeter):
"""Retargeting must resume normally once the grip pose is valid again."""
inputs, outputs = _build_io(retargeter)

_fill_controller(inputs[_DEVICE], grip_valid=False)
retargeter.compute(inputs, outputs, _make_context())

_fill_controller(inputs[_DEVICE], grip_valid=True, position=(0.1, 0.2, 0.3))
retargeter.compute(inputs, outputs, _make_context())

pose = np.from_dlpack(outputs["ee_pose"][0])
npt.assert_array_almost_equal(pose[:3], [0.1, 0.2, 0.3])


class TestSe3RelRetargeterPoseValidity:
@pytest.fixture()
def retargeter(self):
cfg = Se3RetargeterConfig(input_device=_DEVICE)
return Se3RelRetargeter(cfg, name="se3rel")

def test_invalid_grip_emits_zero_delta(self, retargeter):
"""Present-but-invalid grip must not raise and must emit a zero delta."""
inputs, outputs = _build_io(retargeter)

# Establish a baseline with a valid frame first.
_fill_controller(inputs[_DEVICE], grip_valid=True)
retargeter.compute(inputs, outputs, _make_context())

_fill_controller(inputs[_DEVICE], grip_valid=False)
retargeter.compute(inputs, outputs, _make_context())

delta = np.from_dlpack(outputs["ee_delta"][0])
npt.assert_array_almost_equal(delta, np.zeros(6))

def test_recovery_rebaselines_without_jump(self, retargeter):
"""The first valid frame after an invalid stretch must not emit a jump."""
inputs, outputs = _build_io(retargeter)

_fill_controller(inputs[_DEVICE], grip_valid=True)
retargeter.compute(inputs, outputs, _make_context())

_fill_controller(inputs[_DEVICE], grip_valid=False)
retargeter.compute(inputs, outputs, _make_context())

# Controller re-tracks far from the pre-loss baseline.
_fill_controller(inputs[_DEVICE], grip_valid=True, position=(1.0, 1.0, 1.0))
retargeter.compute(inputs, outputs, _make_context())

delta = np.from_dlpack(outputs["ee_delta"][0])
npt.assert_array_almost_equal(delta, np.zeros(6))

def test_invalid_grip_clears_smoothing_state(self, retargeter):
"""Pre-loss motion must not bleed into the output after recovery.

The smoothed-delta EMA buffers must be cleared when the grip pose
goes invalid; otherwise the second valid frame after recovery blends
against stale pre-loss motion.
"""
inputs, outputs = _build_io(retargeter)

# Baseline, then a large motion so the smoothing buffers are nonzero.
_fill_controller(inputs[_DEVICE], grip_valid=True)
retargeter.compute(inputs, outputs, _make_context())
_fill_controller(inputs[_DEVICE], grip_valid=True, position=(0.2, 0.2, 0.2))
retargeter.compute(inputs, outputs, _make_context())

_fill_controller(inputs[_DEVICE], grip_valid=False)
retargeter.compute(inputs, outputs, _make_context())

# Recovery: first valid frame rebaselines, second is stationary and
# must emit zero — any residual comes from stale smoothing state.
_fill_controller(inputs[_DEVICE], grip_valid=True, position=(0.5, 0.5, 0.5))
retargeter.compute(inputs, outputs, _make_context())
_fill_controller(inputs[_DEVICE], grip_valid=True, position=(0.5, 0.5, 0.5))
retargeter.compute(inputs, outputs, _make_context())

delta = np.from_dlpack(outputs["ee_delta"][0])
npt.assert_array_almost_equal(delta, np.zeros(6))
19 changes: 19 additions & 0 deletions src/retargeters/se3_retargeter.py
Original file line number Diff line number Diff line change
Expand Up @@ -249,6 +249,13 @@ def _compute_fn(self, inputs: RetargeterIO, outputs: RetargeterIO, context) -> N
]
)
else:
# A connected controller can report an invalid grip pose (e.g. at
# rest with pose tracking lost) whose zero-norm orientation
# Rotation.from_quat rejects. Hold the last pose, matching the
# is_none path and the hand branch's joint_valid handling.
if not bool(inp[ControllerInputIndex.GRIP_IS_VALID]):
ee_pose[0] = self._last_pose
return
grip_pos = np.from_dlpack(inp[ControllerInputIndex.GRIP_POSITION])
grip_ori = np.from_dlpack(
inp[ControllerInputIndex.GRIP_ORIENTATION]
Expand Down Expand Up @@ -384,6 +391,18 @@ def _compute_fn(self, inputs: RetargeterIO, outputs: RetargeterIO, context) -> N
]
)
else:
# A connected controller can report an invalid grip pose (e.g. at
# rest with pose tracking lost) whose zero-norm orientation
# Rotation.from_quat rejects. Emit a zero delta and, as in the
# reset handler above, re-arm the first-frame baseline and clear
# the smoothing state so the next valid frame neither jumps nor
# blends with pre-loss motion.
if not bool(inp[ControllerInputIndex.GRIP_IS_VALID]):
self._first_frame = True
self._smoothed_delta_pos = np.zeros(3)
self._smoothed_delta_rot = np.zeros(3)
ee_delta[0] = np.zeros(6, dtype=np.float32)
return
Comment thread
hougantc-nvda marked this conversation as resolved.
grip_pos = np.from_dlpack(inp[ControllerInputIndex.GRIP_POSITION])
grip_ori = np.from_dlpack(inp[ControllerInputIndex.GRIP_ORIENTATION])
wrist = np.concatenate([grip_pos, grip_ori])
Expand Down
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