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Python is a high-level, general-purpose programming language that is popular in artificial intelligence. [1] It has a simple, flexible and easily readable syntax. [2] Its popularity results in a vast ecosystem of libraries, including for deep learning, such as PyTorch, TensorFlow, Keras, Google JAX.
Python Robotics (Pyro) is a project designed to create an easy-to-use interface for accessing and controlling a wide variety of real and simulated robots. History
The APIs are accessible via a variety of programming languages, including C++, C#, Python and Java. AirSim supports hardware-in-the-loop with driving wheels and flight controllers such as PX4 for physically and visually realistic simulations. The platform also supports common robotic platforms, such as Robot Operating System (ROS). [6]
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
Webots is a free and open-source 3D robot simulator used in industry, education and research.. The Webots project started in 1996, initially developed by Dr. Olivier Michel at the Swiss Federal Institute of Technology in Lausanne, Switzerland and then from 1998 by Cyberbotics Ltd. as a proprietary licensed software.
Karel is an educational programming language for beginners, created by Richard E. Pattis in his book Karel The Robot: A Gentle Introduction to the Art of Programming. Pattis used the language in his courses at Stanford University, California. The language is named after Karel Čapek, a Czech writer who introduced the word robot in his play R.U ...
The basic ideas for Robot Framework were shaped in Pekka Klärck's masters thesis [3] in 2005. The first version was developed at Nokia Networks the same year. Version 2.0 was released as open source software June 24, 2008 and version 3.0.2 was released February 7, 2017.
Robot learning is a research field at the intersection of machine learning and robotics. It studies techniques allowing a robot to acquire novel skills or adapt to its environment through learning algorithms.
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