The Ultimate Resource for Mobile Robotics: Theory and Practice
- What is the main goal of this book and who is it for? - How is this edition different from the first one? H2: Fundamentals of Mobile Robotics - The mechanical, motor, sensory, perceptual, and cognitive layers of mobile robotics - The challenges and opportunities of mobility in real world environments - The basic concepts and terminology of mobile robotics H2: Locomotion - The different types of locomotion mechanisms and their advantages and disadvantages - The kinematics and dynamics of wheeled, legged, flying, and swimming robots - The control strategies and algorithms for locomotion H2: Perception - The different types of sensors and their characteristics - The signal processing and feature extraction techniques for sensor data - The computer vision and machine learning methods for perception H2: Localization - The problem of estimating the pose and motion of a robot in an unknown environment - The probabilistic framework and Bayesian inference for localization - The landmark-based, map-based, and simultaneous localization and mapping (SLAM) approaches H2: Mapping - The problem of building a representation of the environment from sensor data - The different types of maps and their properties - The occupancy grid, topological, metric, and semantic mapping methods H2: Planning and Navigation - The problem of finding a feasible and optimal path from a start to a goal location - The graph-based, grid-based, and sampling-based planning algorithms - The reactive, deliberative, and hybrid navigation architectures H2: Cognition - The problem of endowing a robot with higher-level reasoning and decision making capabilities - The artificial intelligence and cognitive science paradigms for cognition - The knowledge representation, task planning, learning, and human-robot interaction methods H2: Conclusion - A summary of the main topics covered in the book - A discussion of the current trends and future directions of mobile robotics research - A list of resources and references for further reading H3: FAQs - What are the prerequisites for reading this book? - How can I download the second edition of this book? - What are some examples of autonomous mobile robots in real world applications? - How can I test and implement the algorithms presented in this book? - How can I get involved in the mobile robotics community? Table 2: Article with HTML formatting Introduction to Autonomous Mobile Robots Second Edition
If you are interested in learning about the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers that enable robots to move through real world environments and perform various tasks, then you should definitely check out this book. In this article, we will give you an overview of what this book is about, who it is for, how it is different from the first edition, and how you can download it.
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Fundamentals of Mobile Robotics
Mobile robots are machines that can move autonomously or semi-autonomously in an environment without being fixed to a base or a track. They range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. Mobile robots have many applications in domains such as exploration, transportation, entertainment, agriculture, manufacturing, health care, security, and education.
The main goal of this book is to offer students and other interested readers an introduction to the fundamentals of mobile robotics. It covers all aspects of mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks. These include locomotion, sensing, localization, mapping, planning, navigation, and cognition. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory.
The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers both theoretical and practical aspects of mobile robotics, with examples, exercises, and case studies. It also provides MATLAB code for some of the algorithms presented in the book.
Locomotion
The first aspect of mobility is locomotion, which is the ability of a robot to move from one place to another. Locomotion depends on the type of mechanism that the robot uses to interact with the environment, such as wheels, legs, wings, or propellers. Each type of locomotion has its own advantages and disadvantages in terms of speed, stability, maneuverability, energy efficiency, terrain adaptability, and complexity.
The book introduces the kinematics and dynamics of locomotion, which are the mathematical models that describe the motion and forces of a robot. It also introduces the control strategies and algorithms that are used to regulate the motion and ensure the desired behavior of a robot. The book covers both classical and modern methods for locomotion control, such as PID controllers, feedback linearization, model predictive control, adaptive control, and learning-based control.
Perception
The second aspect of mobility is perception, which is the ability of a robot to acquire information about its environment and itself. Perception relies on the use of sensors, which are devices that convert physical phenomena into electrical signals. Sensors can be classified into two categories: proprioceptive sensors, which measure the internal state of a robot, such as its position, orientation, velocity, acceleration, torque, or temperature; and exteroceptive sensors, which measure the external state of the environment, such as distance, light intensity, color, sound, or magnetic field.
The book introduces the signal processing and feature extraction techniques that are used to process and analyze the sensor data. It also introduces the computer vision and machine learning methods that are used to interpret and understand the sensor data. The book covers both traditional and state-of-the-art methods for perception, such as edge detection, corner detection, optical flow, stereo vision, image segmentation, object recognition, face recognition, scene understanding, speech recognition, natural language processing, and deep learning.
Localization
The third aspect of mobility is localization, which is the ability of a robot to estimate its pose and motion in an unknown environment. Pose refers to the position and orientation of a robot in a coordinate system. Motion refers to the change of pose over time. Localization is essential for a robot to navigate in an environment and perform tasks that require precise positioning.
The book introduces the probabilistic framework and Bayesian inference for localization, which are the mathematical tools that allow a robot to deal with uncertainty and noise in sensor data. It also introduces the landmark-based, map-based, and simultaneous localization and mapping (SLAM) approaches for localization, which are the algorithms that allow a robot to use landmarks, maps, or both to estimate its pose and motion. The book covers both classical and modern methods for localization, such as Kalman filters, particle filters, extended Kalman filters, unscented Kalman filters, graph-based SLAM, and visual SLAM.
Mapping
The fourth aspect of mobility is mapping, which is the ability of a robot to build a representation of the environment from sensor data. Mapping is useful for a robot to plan its path, avoid obstacles, recognize places, and share information with other robots or humans. Mapping can also improve localization by providing prior knowledge about the environment.
The book introduces the different types of maps and their properties, such as occupancy grid maps, topological maps, metric maps, and semantic maps. Occupancy grid maps represent the environment as a grid of cells that indicate whether each cell is occupied or free. Topological maps represent the environment as a graph of nodes and edges that indicate landmarks and connections between them. Metric maps represent the environment as a set of geometric features that indicate shapes and positions of objects. Semantic maps represent the environment as a set of symbolic labels that indicate meanings and relations of objects.
The book also introduces the occupancy grid, topological, metric, and semantic mapping methods, which are the algorithms that allow a robot to construct maps from sensor data. The book covers both classical and modern methods for mapping, such as Bayesian mapping, histogram filter mapping, Markov chain Monte Carlo mapping, graph optimization mapping, and deep learning mapping.
Planning and Navigation
The fifth aspect of mobility is planning and navigation, which is the ability of a robot to find a feasible and optimal path from a start to a goal location. Planning and navigation depend on the type of map that the robot uses to represent the environment, such as occupancy grid, topological, metric, or semantic maps. Each type of map has its own advantages and disadvantages in terms of accuracy, completeness, scalability, and usability.
The book introduces the graph-based, grid-based, and sampling-based planning algorithms, which are the methods that allow a robot to search for a path on a map. It also introduces the reactive, deliberative, and hybrid navigation architectures, which are the frameworks that allow a robot to execute a path and avoid dynamic obstacles. The book covers both classical and modern methods for planning and navigation, such as A*, D*, RRT, PRM, VFH, DWA, EKF-SLAM, and FastSLAM.
Cognition
The sixth aspect of mobility is cognition, which is the ability of a robot to endow with higher-level reasoning and decision making capabilities. Cognition enables a robot to perform complex tasks that require knowledge, goals, plans, learning, and interaction. Cognition also enables a robot to adapt to changing environments and situations, and to cooperate with other robots or humans.
The book introduces the artificial intelligence and cognitive science paradigms for cognition, which are the theoretical foundations that inspire and guide the design of cognitive robots. It also introduces the knowledge representation, task planning, learning, and human-robot interaction methods, which are the techniques that implement the cognitive functions of a robot. The book covers both traditional and state-of-the-art methods for cognition, such as logic, ontologies, STRIPS, PDDL, reinforcement learning, supervised learning, unsupervised learning, imitation learning, natural language processing, speech synthesis, gesture recognition, facial expression recognition, and emotion recognition.
Conclusion
In this article, we have given you an overview of the book "Introduction to Autonomous Mobile Robots Second Edition", which is a comprehensive and up-to-date textbook on the fundamentals of mobile robotics. The book covers all aspects of mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks. These include locomotion, perception, localization, mapping, planning, navigation, and cognition. The book synthesizes material from various fields, such as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents both theoretical and practical aspects of mobile robotics, with examples, exercises, and case studies. It also provides MATLAB code for some of the algorithms presented in the book.
The book is suitable for undergraduate and graduate students who want to learn about mobile robotics, as well as for researchers and practitioners who want to update their knowledge on the latest developments in this field. The book assumes some basic knowledge of linear algebra, calculus, probability theory, and programming. The book is also accompanied by a website that contains additional resources and information.
If you are interested in reading this book, you can download it from MIT Press or Google Play Books. You can also find more information about the authors and their research on their personal websites: Roland Siegwart, Illah Reza Nourbakhsh, and Davide Scaramuzza.
FAQs
What are the prerequisites for reading this book?
The book assumes some basic knowledge of linear algebra, calculus, probability theory, and programming. However, the book also provides some review and appendix sections that cover some of the necessary background material.
How can I download the second edition of this book?
You can download it from MIT Press or Google Play Books. You can also access the online version of the book from IEEE Xplore.
What are some examples of autonomous mobile robots in real world applications?
Some examples are the Mars rovers that explore the surface of Mars, the self-driving cars that navigate in urban environments, the drones that deliver packages or monitor crops, the vacuum cleaners that clean the floors of homes and offices, the humanoid robots that assist in disaster response or entertainment, and the social robots that interact with humans in various settings.
How can I test and implement the algorithms presented in this book?
The book provides MATLAB code for some of the algorithms presented in the book, which you can download from the book's website. You can also use other programming languages or frameworks, such as Python, C++, ROS, or Gazebo, to implement and test the algorithms on your own computer or robot.
How can I get involved in the mobile robotics community?
You can join some of the professional associations or societies that are related to mobile robotics, such as IEEE Robotics and Automation Society, ACM Special Interest Group on Artificial Intelligence, or International Federation of Robotics. You can also attend some of the conferences or workshops that are related to mobile robotics, such as IEEE International Conference on Robotics and Automation, IEEE/RSJ International Conference on Intelligent Robots and Systems, Robotics: Science and Systems, or International Symposium on Robotics Research. You can also follow some of the journals or magazines that are related to mobile robotics, such as IEEE Transactions on Robotics, Autonomous Robots, Robotics and Autonomous Systems, or IEEE Robotics and Automation Magazine.
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