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Introductiontoautonomousmobilerobotssecondeditiondownload
Second edition of a comprehensive introduction to all aspects of mobile robotics, from algorithms to mechanisms. The first edition covered the general field of robotics, including the field of AR (automated image processing) and was supplemented with many specific examples, including those for ROBOKIT in a compact and convenient form.
The publication will be useful both for experienced robotics specialists and for those who are just starting their studies and are interested in the latest developments in this area.
The 2nd Edition includes detailed reviews of the software, data exchange between all major existing devices and sensors, and a comprehensive list of models that are the most popular on the market (over 200), a list of manufacturers and provided with a large number of samples and data examples.
In particular, this edition details image generation for inverse problem modeling:
* All devices that can be controlled from the same sensor and output system have completely different image formats. Only a few of them are the most common.
Some examples can be divided into two groups: basic and specialized. In the first case, the most common 2D and 3D models are considered, specialized examples will be devoted to digital paintings, consisting of a set of pixels used to create an image.
In the second case, different approaches to creating images are considered, which use different tools and technologies.
In addition, the publication also covers some of the applications of AR in robotics, from standard data collection solutions for direct transfer to an industrial computer (Rigetti-Bolz & Tinkle), to intuitive motion programming using Arduino Mega controllers that allow you to create motion, without using a workaround.
The various methods of teaching basic technologies are very informative and fully described:
* Robots are created to solve specific tasks that are assigned to the robot, but the methods used for this can vary greatly for different types of robots.
In a nutshell, we can say that an integrated approach to learning consists of two stages: in the process of creating program algorithms and in the process of their automatic debugging.
At the first stage, the robots must go through a preliminary (training) process of learning the algorithm of actions in real conditions, this stage is called the “Blind Games†method, a general algorithm is developed, with the help of which many different situations are created, the possible solutions in which are determined by the algorithms. In the second step after learning the algorithms, there may be questions that need
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