marinholab-sas-core
Python bindings for the ROS-free SmartArmStack C++ core.
This repository wraps MarinhoLab/sas_cpp (the pure-C++ part of SmartArmStack/sas_core) with pybind11, exposing it to Python as the
marinholab.sas.corepackage.More information about SmartArmStack is available in smartarmstack.github.io.
Contents
marinholab/sas/core/— the Python package._core.*— compiled pybind11 extension (the C++ bindings live insrc/).modeling/— kinematic modeling bindings (re-exported from_core).papers/— reference implementations from published work.papers/icra2019/— the task-spaceController(RCM + joint-limit constraints as a QP) from "A Unified Framework for the Teleoperation of Surgical Robots in Constrained Workspaces" (ICRA 2019).
example_*.py— example scripts (also installed as commands).
src/— the C++ binding sources (ported fromSmartArmStack/sas_core).submodules/sas_cpp— the C++ core (git submodule, consumed via CMake).submodules/dqrobotics_cpp— the dqrobotics C++ library (git submodule, pinned to the commit the requireddqroboticsPython release is built from).submodules/pybind11— pybind11 (git submodule, pinned to v3.0.4).docker/—ubuntu:noblebuild environment and full test pipeline.
The C++ core depends on Eigen3 and dqrobotics. dqrobotics is compiled
from the submodules/dqrobotics_cpp submodule and linked statically into the
extension module, together with the C++ core, so no dqrobotics library needs
to be installed. The Python package additionally depends on the dqrobotics
Python package, which registers the dual-quaternion and robot-model types the
bindings expose (pybind11 shares them between the two extension modules, so
the submodule is kept at the same dqrobotics/cpp commit as that release).
Installation
From PyPI, with wheels for Python 3.10–3.14 on Linux (x86_64, aarch64), macOS (arm64, 14.0 or later) and Windows (x86_64):
pip install marinholab-sas-core
The wheels match the Python versions that dqrobotics publishes wheels for,
in its pre-releases, which the requirement dqrobotics>=26.4.0a7 selects.
From source:
git clone --recursive https://github.com/MarinhoLab/sas_py.git
cd sas_py
pip install . --no-build-isolation
Building requires cmake (>= 3.16), ninja, a C++17 compiler and Eigen3.
On Debian/Ubuntu:
sudo apt install build-essential g++ cmake ninja-build python3-dev libeigen3-dev
On macOS, with Eigen from Homebrew:
brew install eigen cmake ninja
CMAKE_ARGS="-DCMAKE_PREFIX_PATH=$(brew --prefix)" pip install . --no-build-isolation
On Windows, Eigen comes from vcpkg, expected at C:/vcpkg
(vcpkg install eigen3:x64-windows).
Usage
from marinholab.sas.core import (
Clock,
Statistics,
RobotDriver,
ShutdownSignaler,
)
# High-resolution sampling clock
clock = Clock(0.01) # 10 ms sampling period
clock.init()
for _ in range(100):
clock.update_and_sleep()
print(clock.get_statistics(Statistics.Mean, Clock.TimeType.Computational))
# Subclass RobotDriver to drive hardware
class MyDriver(RobotDriver):
def __init__(self, ss):
super().__init__(ss)
def get_joint_positions(self):
return np.zeros(6)
def set_target_joint_positions(self, target):
...
def connect(self):
...
def disconnect(self):
...
def initialize(self):
...
def deinitialize(self):
...
Kinematic modeling
import numpy as np
from dqrobotics import DQ
from marinholab.sas.core import SerialManipulatorSimulatorFriendly
# 3 revolute joints about X, Y, Z with zero per-joint offsets.
arm = SerialManipulatorSimulatorFriendly(
offset_before=[DQ([1]), DQ([1]), DQ([1])],
offset_after=[DQ([1]), DQ([1]), DQ([1])],
actuation_types=[
SerialManipulatorSimulatorFriendly.ActuationType.RX,
SerialManipulatorSimulatorFriendly.ActuationType.RY,
SerialManipulatorSimulatorFriendly.ActuationType.RZ,
],
)
q = np.array([0.1, -0.2, 0.3])
x = arm.raw_fkm(q, 2) # dual-quaternion pose of the end-effector
J = arm.raw_pose_jacobian(q, 2) # 8 x 3 pose Jacobian
The examples are installed as commands:
sas_core_clock_example— a 10 msClockwith timing statistics.sas_core_clock_sched_fifo_example— a 1 msClockunderSCHED_FIFO.sas_core_robot_driver_subclass_example— subclassRobotDriverin Python and exercise the trampoline (connect / initialize / targets / limits).
Versioning
The version is computed from git tags at build time by
setuptools-git-versioning. A monthly version tag of the form YY.MM
(e.g. 26.09) plus the number of commits since that tag yields a rolling
YY.MM.NN version (e.g. 26.09.3), mirroring MarinhoLab/sas_cpp.
An untagged checkout builds as 0.0.1 (a development version).
Testing
A full build + test pipeline runs in an ubuntu:noble container:
cd docker
docker compose run --rm marinholab_sas_core
License
See LICENSE for details (LGPLv3).
Metadata
Release files for marinholab-sas-core 26.9.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 4.6 MB
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| Size | 169.9 kB |
| Tags | CPython 3.10 macOS 14.0+ ARM64 |
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