Python has become a popular language in robotics due to its ease of use and extensive libraries. Here are some commonly used Python libraries:
Robot Operating System (ROS)
While a framework, ROS has extensive Python libraries (rospy) for robotics development.
PyRobot
A library from Facebook AI Research for robot learning and experimentation.
Robotics Toolbox for Python (RTPy)
Provides tools for kinematics, dynamics, trajectory planning, and control.
PyDy (Python Dynamics)
A toolkit for modeling and simulating multibody dynamics.
Klamp’t
A comprehensive package for robot modeling, simulation, planning, and control with Python bindings.
PyBullet
A Python module for physics simulation often used for robotics.
Open3D
Supports rapid development of software dealing with 3D data, useful for point cloud processing.
CV2 (OpenCV)
Python bindings for OpenCV, crucial for computer vision tasks in robotics.
Robot Framework
Automation framework usable for robotic process automation and testing.
robotic (Marc Toussaint’s library)
Python library for operating real or simulated robots and solving constrained optimization problems.
PythonRobotics
Collection of Python sample codes for various robotics algorithms (educational purposes).
Other Languages (Briefly Mentioned):
- C++: Dominant for performance and low-level control (ROS, RL, OMPL, Gazebo, MoveIt!, PCL, Eigen, etc.).
- MATLAB: Used in academia and control systems (Robotics System Toolbox). Robotics System Toolbox
- Julia: Growing interest with libraries like RigidBodyDynamics.jl.
The choice of library depends on the specific robotics task, performance needs, and developer preference.
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