newton-actuators
DEPRECATED: actuators are now part of the 'newton' package as 'newton.actuators'. This standalone package is no longer maintained.
Decision gist · record as of 2026-08-14
No—do not install. The package is explicitly deprecated and unmaintained as of Newton 1.3. The same functionality is now available in the main newton package as newton.actuators. Migrate to that instead to receive ongoing maintenance and updates.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires warp-lang as a runtime dependency; CUDA 12.x or 13.x for GPU execution; PyTorch optional but required for ActuatorNetMLP and ActuatorNetLSTM.
- Low friction wheel install.
- Package is marked inactive (Development Status 7) and explicitly deprecated in favor of the built-in newton.actuators module starting with Newton 1.3; no longer maintained.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with attribution; no restrictions on derivative works or distribution.
last release 2026-05-29 (77 days) · last repo commit 2026-08-14 · 5,349 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 140,237 downloads/mo, #11,275 on PyPI
Alternatives
Verify before relying
pip install newton-actuators
import warp as wp
from newton_actuators import ActuatorPD
indices = wp.array([0, 1, 2], dtype=wp.uint32)
pd = ActuatorPD(
input_indices=indices,
output_indices=indices,
kp=wp.array([100.0, 100.0, 100.0], dtype=wp.float32),
kd=wp.array([10.0, 10.0, 10.0], dtype=wp.float32),
max_force=wp.array([50.0, 50.0, 50.0], dtype=wp.float32),
)
pd.step(sim_state, sim_control, None, None, dt=0.01)- Whether existing code using newton-actuators will continue to work with future Newton releases or if migration is urgent.
- Compatibility details between this 0.1.1 release and the newton.actuators module it is being superseded by.
- Whether PyTorch extras (torch-cu12, torch-cu13) are still available or have been removed.
What it is and what it does
Newton Actuators is a GPU-accelerated library for computing control forces and torques in physics simulations. It provides seven actuator classes ranging from simple stateless PD controllers to stateful PID, delayed PD, DC motor models, and neural network actuators (MLP and LSTM). Each actuator reads from simulation state arrays and writes computed forces back to control arrays, with support for both CUDA-graphable and non-graphable execution paths.
The library is built on top of warp-lang for GPU acceleration and optionally integrates PyTorch for neural network actuators. However, the package is now deprecated: starting with Newton 1.3, all actuators have been moved into the main newton package as newton.actuators, and this standalone distribution is no longer maintained. Existing users should migrate to the built-in module.
Use it for
- Implementing PD or PID feedback control for robotic joint actuators in GPU-accelerated physics simulations.
- Modeling DC motor dynamics with velocity-dependent torque saturation in physics pipelines.
- Using learned neural network policies (MLP or LSTM) as actuators to drive simulation control.
- Parsing actuator definitions from USD files and instantiating the appropriate control law.
- Running stateful control loops with double-buffered state management in CUDA graphs.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No—do not install.
The package is explicitly deprecated and unmaintained as of Newton 1.3. The same functionality is now available in the main newton package as newton.actuators. Migrate to that instead to receive ongoing maintenance and updates.
Install
newton-actuators on PyPI
Before you install
Low friction wheel install. Package is marked inactive (Development Status 7) and explicitly deprecated in favor of the built-in newton.actuators module starting with Newton 1.3; no longer maintained.
Requires warp-lang as a runtime dependency; CUDA 12.x or 13.x for GPU execution; PyTorch optional but required for ActuatorNetMLP and ActuatorNetLSTM.
License in practice
Apache-2.0 permissive license allows commercial and private use with attribution; no restrictions on derivative works or distribution.
Quickstart
pip install newton-actuators
import warp as wp
from newton_actuators import ActuatorPD
indices = wp.array([0, 1, 2], dtype=wp.uint32)
pd = ActuatorPD(
input_indices=indices,
output_indices=indices,
kp=wp.array([100.0, 100.0, 100.0], dtype=wp.float32),
kd=wp.array([10.0, 10.0, 10.0], dtype=wp.float32),
max_force=wp.array([50.0, 50.0, 50.0], dtype=wp.float32),
)
pd.step(sim_state, sim_control, None, None, dt=0.01)Verify before relying
- Whether existing code using newton-actuators will continue to work with future Newton releases or if migration is urgent.
- Compatibility details between this 0.1.1 release and the newton.actuators module it is being superseded by.
- Whether PyTorch extras (torch-cu12, torch-cu13) are still available or have been removed.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagewarp-lang |
| Maintenance | Actively maintained 77 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 140,237 / month, #11,275 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 7 - InactiveEnvironment :: GPU :: NVIDIA CUDAProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12 |
Evidence: newton_actuators-0.1.1-py3-none-any.whl
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See also newton · dynamixel-sdk · mujoco-warp · nvidia-cudnn-cu12 · newton-usd-schemas · nvidia-cudnn-cu11 · nvidia-cudnn-cu13 · simple-pid · nvidia-cusolver-cu11 · cpm-kernels