Currently, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia. The book encompasses the kinematic and dynamic modelling, analysis, design, and control of mechatronic and robotic systems, with the scope of improving their performance, as well as simulating and testing novel devices and control architectures. A broad range of disciplines and topics are included, such as robotic manipulation, mobile systems, cable-driven robots, wearable and rehabilitation devices, variable stiffness safety-oriented mechanisms, optimization of robot performance, and energy-saving systems.

In modern times, mechatronic and robotic systems are developing at a faster pace than in the past, and research on novel solutions and applications of such devices are studied in both industrial and academic environments. The second volume of this Special Issue of Applied Sciences aims to disseminate the latest research achievements, ideas, and applications of the modeling and control of mechatronic and robotic systems, with particular emphasis on novel trends and challenges. We invited contributions to this Special Issue on topics including (but not limited to): modeling and control, path and trajectory planning, optimization problems, collaborative robotics, mechatronics, flexible multi-body systems, mobile robotics, and manufacturing applications.

Currently, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia. The book encompasses the kinematic and dynamic modelling, analysis, design, and control of mechatronic and robotic systems, with the scope of improving their performance, as well as simulating and testing novel devices and control architectures. A broad range of disciplines and topics are included, such as robotic manipulation, mobile systems, cable-driven robots, wearable and rehabilitation devices, variable stiffness safety-oriented mechanisms, optimization of robot performance, and energy-saving systems.

A practical methodology for designing integrated automation control for systems and processes Implementing digital control within mechanical-electronic (mechatronic) systems is essential to respond to the growing demand for high-efficiency machines and processes. In practice, the most efficient digital control often integrates time-driven and event-driven characteristics within a single control scheme. However, most of the current engineering literature on the design of digital control systems presents discrete-time systems and discrete-event systems separately. Control Of Mechatronic Systems: Model-Driven Design And Implementation Guidelines unites the two systems, revisiting the concept of automated control by presenting a unique practical methodology for whole-system integration. With its innovative hybrid approach to the modeling, analysis, and design of control systems, this text provides material for mechatronic engineering and process automation courses, as well as for self-study across engineering disciplines. Real-life design problems and automation case studies help readers transfer theory to practice, whether they are building single machines or large-scale industrial systems. Presents a novel approach to the integration of discrete-time and discrete-event systems within mechatronic systems and industrial processes Offers user-friendly self-study units, with worked examples and numerous real-world exercises in each chapter Covers a range of engineering disciplines and applies to small- and large-scale systems, for broad appeal in research and practice Provides a firm theoretical foundation allowing readers to comprehend the underlying technologies of mechatronic systems and processes Control Of Mechatronic Systems is an important text for advanced students and professionals of all levels engaged in a broad range of engineering disciplines.

A comprehensive review of the principles and dynamics of robotic systems Dynamics and Control of Robotic Systems offers a systematic and thorough theoretical background for the study of the dynamics and control of robotic systems. The authors—noted experts in the field—highlight the underlying principles of dynamics and control that can be employed in a variety of contemporary applications. The book contains a detailed presentation of the precepts of robotics and provides methodologies that are relevant to realistic robotic systems. The robotic systems represented include wide range examples from classical industrial manipulators, humanoid robots to robotic surgical assistants, space vehicles, and computer controlled milling machines. The book puts the emphasis on the systematic application of the underlying principles and show how the computational and analytical tools such as MATLAB, Mathematica, and Maple enable students to focus on robotics’ principles and theory. Dynamics and Control of Robotic Systems contains an extensive collection of examples and problems and: Puts the focus on the fundamentals of kinematics and dynamics as applied to robotic systems Presents the techniques of analytical mechanics of robotics Includes a review of advanced topics such as the recursive order N formulation Contains a wide array of design and analysis problems for robotic systems Written for students of robotics, Dynamics and Control of Robotic Systems offers a comprehensive review of the underlying principles and methods of the science of robotics.

Modern robotic systems are tied to operate autonomously in real-world environments performing a variety of complex tasks. Autonomous robots must rely on fundamental capabilities such as locomotion, trajectory tracking control, multi-sensor fusion, task/path planning, navigation, and real-time perception. Combining this knowledge is essential to design rolling, walking, aquatic, and hovering robots that sense and self-control. This book contains a mathematical modelling framework to support the learning of modern robotics and mechatronics, aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. The volume exposes a solid understanding of mathematical methods as a common modelling framework to properly interpret advanced robotic systems. Including numerical approximations, solution of linear and non-linear systems of equations, curves fitting, differentiation and integration of functions. The book is suitable for courses on robotics, mechatronics, sensing models, vehicles design and control, modelling, simulation, and mechanisms analysis. It is organised with 17 chapters divided in five parts that conceptualise classical mechanics to model a wide variety of applied robotics. It comprehends a hover-craft, an amphibious hexapod, self-reconfiguration and under-actuation of rolling and passive walking robots with Hoekens, Klann, and Jansen limbs for bipedal, quadruped, and octapod robots.

As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems.