diff --git a/docs/modules/1_introduction/2_python_for_robotics/python_for_robotics_main.rst b/docs/modules/1_introduction/2_python_for_robotics/python_for_robotics_main.rst index 1ad5316f53..2f89f0c7b5 100644 --- a/docs/modules/1_introduction/2_python_for_robotics/python_for_robotics_main.rst +++ b/docs/modules/1_introduction/2_python_for_robotics/python_for_robotics_main.rst @@ -1,11 +1,13 @@ Python for Robotics ---------------------- +This section explains the Python itself and features for Robotics. + Python for general-purpose programming ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `Python `_ is an general-purpose programming language developed by -`Guido van Rossum `_ in the late 1980s. +`Guido van Rossum `_ from the late 1980s. It features as follows: @@ -17,7 +19,7 @@ It features as follows: #. Batteries included #. Interoperability for C and Fortran -Due to these features, Python is the most popular programming language +Due to these features, Python is one of the most popular programming language for educational purposes for programming beginners. Python for Scientific Computing @@ -29,9 +31,9 @@ For example, #. High-level and interpreted features enable scientists to focus on their problems without dealing with low-level programming tasks like memory management. #. Code readability, rapid prototyping, and batteries included features enables scientists who are not professional programmers, to solve their problems easily. -#. The interoperability to wrap C and Fortran libraries enables scientists to access already existed powerful scientific computing libraries. +#. The interoperability to wrap C and Fortran libraries enables scientists to access already existed powerful and optimized scientific computing libraries. -To address the more needs of scientific computing, many libraries have been developed. +To address the more needs of scientific computing, many fundamental scientific computation libraries have been developed based on the upper features. - `NumPy `_ is the fundamental package for scientific computing with Python. - `SciPy `_ is a library that builds on NumPy and provides a large number of functions that operate on NumPy arrays and are useful for different types of scientific and engineering applications. @@ -39,12 +41,55 @@ To address the more needs of scientific computing, many libraries have been deve - `Pandas `_ is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation library built on top of NumPy. - `SymPy `_ is a Python library for symbolic mathematics. -And more domain-specific libraries have been developed: +Also, more domain-specific libraries have been developed based on these fundamental libraries: + - `Scikit-learn `_ is a free software machine learning library for the Python programming language. - `Scikit-image `_ is a collection of algorithms for image processing. +- `Networkx `_ is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. +- `SunPy `_ is a community-developed free and open-source software package for solar physics. +- `Astropy `_ is a community-developed free and open-source software package for astronomy. + +Currently, Python is one of the most popular programming languages for scientific computing. Python for Robotics ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -TBD +Scientific computation routine are very important for robotics. +For example, matrix operation, optimization, and visualization are fundamental for robotics. + +Python has become an increasingly popular language in robotics due to its versatility, readability, and extensive libraries. Here's a breakdown of why Python is a great choice for robotics development: + +Advantages of Python for Robotics: + +Simplicity and Readability: Python's syntax is clear and concise, making it easier to learn and write code. This is crucial in robotics where complex algorithms and control logic are involved. +Extensive Libraries: Python boasts a rich collection of libraries specifically designed for robotics: +ROS (Robot Operating System): ROS, a widely used framework for robotics development, has strong Python support (rospy). This allows developers to easily create nodes, manage communication between different parts of a robot system, and utilize various ROS tools. +OpenCV: This powerful library provides tools for computer vision tasks like image processing, object detection, and motion tracking, essential for robots that perceive and interact with their environment. +NumPy and SciPy: These libraries offer efficient numerical computation and scientific tools, enabling developers to implement complex mathematical models and control algorithms. +Scikit-learn: This library provides machine learning algorithms, which are increasingly important in robotics for tasks like perception, planning, and control. +Cross-Platform Compatibility: Python code can run on various operating systems (Windows, macOS, Linux), providing flexibility in choosing hardware platforms for robotics projects. +Large Community and Support: Python has a vast and active community, offering ample resources, tutorials, and support for developers. This is invaluable when tackling challenges in robotics development. +Use Cases of Python in Robotics: + +Robot Control: Python can be used to write control algorithms for robot manipulators, mobile robots, and other robotic systems. +Perception: Python, combined with libraries like OpenCV, enables robots to process sensor data (camera images, lidar data) to understand their surroundings. +Path Planning: Python algorithms can be used to plan collision-free paths for robots to navigate in complex environments. +Machine Learning: Python libraries like Scikit-learn empower robots to learn from data and improve their performance in tasks like object recognition and manipulation. +Simulation: Python can be used to create simulated environments for testing and developing robot algorithms before deploying them on real hardware. +Examples of Python in Robotics: + +Autonomous Navigation: Python is used in self-driving cars and other autonomous vehicles for tasks like perception, localization, and path planning. +Industrial Robotics: Python is employed in manufacturing for robot control, quality inspection, and automation. +Service Robotics: Python powers robots that perform tasks like cleaning, delivery, and customer service in various environments. +Research and Education: Python is a popular choice in robotics research and education due to its ease of use and versatility. +Getting Started with Python in Robotics: + +Learn Python Basics: Familiarize yourself with Python syntax, data structures, and programming concepts. +Explore Robotics Libraries: Dive into libraries like ROS, OpenCV, and others relevant to your robotics interests. +Practice with Projects: Start with small projects to gain hands-on experience, gradually increasing complexity. +Join the Community: Engage with the robotics community through online forums, workshops, and conferences to learn from others and share your knowledge. +In conclusion, Python's simplicity, extensive libraries, and strong community support make it an ideal language for robotics development. Whether you're a beginner or an experienced programmer, Python offers the tools and resources you need to build innovative and capable robots. + +Python is used for this `PythonRobotics` project because of the above features +to achieve the purpose of this project described in the :ref:`What is PythonRobotics?`.