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Merge pull request #247 from NVlabs/fix_trajectory_evaluation
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balakumar-s committed Apr 30, 2024
2 parents 1e0b5a8 + e6a5ab2 commit 7196be7
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6 changes: 6 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -10,6 +10,12 @@ its affiliates is strictly prohibited.
-->
# Changelog

## Latest Commit

### BugFixes & Misc.
- Fix bug in evaluator to account for dof maximum acceleration and jerk.
- Add unit test for different acceleration and jerk limits.

## Version 0.7.2

### New Features
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4 changes: 3 additions & 1 deletion src/curobo/types/state.py
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Expand Up @@ -81,7 +81,7 @@ def __post_init__(self):
@staticmethod
def from_numpy(
joint_names: List[str],
position: np.ndarry,
position: np.ndarray,
velocity: Optional[np.ndarray] = None,
acceleration: Optional[np.ndarray] = None,
jerk: Optional[np.ndarray] = None,
Expand All @@ -91,6 +91,8 @@ def from_numpy(
vel = acc = je = None
if velocity is not None:
vel = tensor_args.to_device(velocity)
else:
vel = pos * 0.0
if acceleration is not None:
acc = tensor_args.to_device(acceleration)
else:
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5 changes: 3 additions & 2 deletions src/curobo/wrap/reacher/evaluator.py
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Expand Up @@ -218,12 +218,13 @@ def compute_smoothness(
scale_dt = (1 / dt_score).view(-1, 1, 1)
abs_acc = torch.abs(acc) * (scale_dt**2)
# mean_acc_val = torch.max(torch.mean(abs_acc, dim=-1), dim=-1)[0]
max_acc_val = torch.max(torch.max(abs_acc, dim=-1)[0], dim=-1)[0]
max_acc_val = torch.max(abs_acc, dim=-2)[0] # batch x dof
abs_jerk = torch.abs(jerk) * scale_dt**3
# calculate max mean jerk:
# mean_jerk_val = torch.max(torch.mean(abs_jerk, dim=-1), dim=-1)[0]
max_jerk_val = torch.max(torch.max(abs_jerk, dim=-1)[0], dim=-1)[0]
max_jerk_val = torch.max(abs_jerk, dim=-2)[0] # batch x dof
acc_label = torch.logical_and(max_acc_val <= max_acc, max_jerk_val <= max_jerk)
acc_label = torch.all(acc_label, dim=-1)
return (acc_label, smooth_cost(abs_acc, abs_jerk, dt_score))


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72 changes: 72 additions & 0 deletions tests/motion_gen_eval_test.py
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@@ -0,0 +1,72 @@
#
# Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
# property and proprietary rights in and to this material, related
# documentation and any modifications thereto. Any use, reproduction,
# disclosure or distribution of this material and related documentation
# without an express license agreement from NVIDIA CORPORATION or
# its affiliates is strictly prohibited.
#

# Third Party
import pytest
import torch

# CuRobo
from curobo.types.base import TensorDeviceType
from curobo.types.robot import JointState
from curobo.util_file import get_robot_configs_path, join_path, load_yaml
from curobo.wrap.reacher.evaluator import TrajEvaluatorConfig
from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig, MotionGenPlanConfig


def run_motion_gen(robot_file, evaluate_interpolated_trajectory, max_acc, max_jerk):
tensor_args = TensorDeviceType()
world_file = "collision_test.yml"
robot_data = load_yaml(join_path(get_robot_configs_path(), robot_file))
dof = len(robot_data["robot_cfg"]["kinematics"]["cspace"]["joint_names"])

robot_data["robot_cfg"]["kinematics"]["cspace"]["max_acceleration"] = [
max_acc for i in range(9)
]
robot_data["robot_cfg"]["kinematics"]["cspace"]["max_jerk"] = [max_jerk for i in range(9)]

motion_gen_config = MotionGenConfig.load_from_robot_config(
robot_data,
world_file,
tensor_args,
use_cuda_graph=False,
maximum_trajectory_dt=1.5,
evaluate_interpolated_trajectory=evaluate_interpolated_trajectory,
)
motion_gen = MotionGen(motion_gen_config)

retract_cfg = motion_gen.get_retract_config()

start_state = JointState.from_position(retract_cfg.view(1, -1).clone())
goal_state = JointState.from_position(retract_cfg.view(1, -1).clone() + 0.2)

result = motion_gen.plan_single_js(
start_state, goal_state, MotionGenPlanConfig(max_attempts=5, enable_graph_attempt=10)
)
return result


@pytest.mark.parametrize(
"robot_file, evaluate_interpolated_traj, max_acc, max_jerk",
[
("franka.yml", False, 1.0, 500.0),
("franka.yml", True, 0.1, 500.0),
("franka.yml", True, 1.0, 500.0),
("ur5e.yml", False, 1.0, 500.0),
("ur5e.yml", True, 0.1, 500.0),
("ur5e.yml", True, 1.0, 500.0),
],
)
def test_motion_gen_trajectory(robot_file, evaluate_interpolated_traj, max_acc, max_jerk):
result = run_motion_gen(robot_file, evaluate_interpolated_traj, max_acc, max_jerk)

assert result.success.item()
assert torch.max(torch.abs(result.optimized_plan.acceleration)) <= max_acc
assert torch.max(torch.abs(result.optimized_plan.jerk)) <= max_jerk

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