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Introduction to Autonomous Robots

Introduction to Autonomous Robots

Introduction to Autonomous Robots Description

This book gives students with a sophomore level of linear algebra and probability theory an algorithmic perspective on autonomous robots. Robotics is a new field that combines mechanical engineering, electrical engineering, and computer science. As computers get more powerful, making robots intelligent becomes a greater focus of attention, and robotics research’s most difficult frontier. While there are several textbooks available to sophomore-level undergraduates on the physics and dynamics of robots, books that provide a wide algorithmic approach are usually relegated to the graduate level. This book was created not to create “yet another textbook, but better than the others,” but to allow us to teach robotics to third and fourth year undergraduates at the University of Colorado’s Department of Computer Science.

Although they are classified as “Artificial Intelligence,” typical AI techniques are insufficient for dealing with problems involving uncertainty, such as a robot’s interaction in the real world. The kinematic equations of manipulators and mobile robots are developed using simple trigonometry in this text, which subsequently introduces path planning, sensing, and uncertainty. The robot localization problem is formalised by defining error propagation, which leads to Markov localization, particle filtering, and finally the Extended Kalman Filter and Simultaneous Localization and Mapping. Instead of focusing on cutting-edge solutions to a specific sub-issue, the book focuses on a gradual step-by-step development of concepts through recurring examples that encapsulate the essence of a problem. The solutions mentioned may not be the greatest, but they are simple to understand and commonly used in the community. Odometry and line-fitting, for example, are used to illustrate forward kinematics and least-squares solutions, and later serve as inspiring examples for error propagation and the Kalman filter in a localization context.

Notably, the book is expressly robot-agnostic, underlining the importance of fundamental concepts in today’s world. Rather, a variety of project-based curricula are described in an Appendix and made available online, ranging from a maze-solving competition that can be realised with most camera-equipped differential-wheel robots to manipulation experiments with a robotic arm, all of which can be entirely conducted in simulation to teach the majority of the core concepts.
This free book is distributed under the terms of the Creative Commons License (CC BY-NC-ND). You may get the Introduction to Autonomous Robots ebook in PDF format for free (13.3 MB).

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