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This monograph presents the development of novel model-based methodologies for engineering self-organized and self-assembled systems. The work bridges the gap between statistical mechanics and control theory by tackling a number of challenges for a class of distributed systems involving a specific type of constitutive components, namely referred to as Smart Minimal Particles. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities.
Developments in bio-inspired computation have impacted multiple fields and created opportunities for new applications. In recent years, these techniques have been increasingly integrated into robotic systems. Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities is an innovative reference source for the latest perspectives on biologically-inspired computation techniques for robot design and control. Highlighting a range of pivotal topics such as software engineering, simulation tools, and robotic security, this book is ideally designed for researchers, academics, students, and practitioners interested in the role of membrane computing in mobile robots.
Distributed robotics is a rapidly growing, interdisciplinary research area lying at the intersection of computer science, communication and control systems, and electrical and mechanical engineering. The goal of the Symposium on Distributed Autonomous Robotic Systems (DARS) is to exchange and stimulate research ideas to realize advanced distributed robotic systems. This volume of proceedings includes 43 original contributions presented at the Tenth International Symposium on Distributed Autonomous Robotic Systems (DARS 2010), which was held in November 2010 at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. The selected papers in this volume are authored by leading researchers from Asia, Europa, and the Americas, thereby providing a broad coverage and perspective of the state-of-the-art technologies, algorithms, system architectures, and applications in distributed robotic systems. The book is organized into four parts, each representing one critical and long-term research thrust in the multi-robot community: distributed sensing (Part I); localization, navigation, and formations (Part II); coordination algorithms and formal methods (Part III); modularity, distributed manipulation, and platforms (Part IV).
Great interest is now focused on distributed autonomous robotic systems (DARS) as a new strategy for the realization of flexible, robust, and intelligent robots. Inspired by autonomous, decentralized, and self-organizing biological systems, the field of DARS encompasses broad interdisciplinary technologies related not only to robotics and computer engineering but also to biology and psychology. The rapidly growing interest in this new area of research was manifest in the first volume of Distributed Autonomous Robotic Systems, published in 1994. This second volume in the series presents the most recent work by eminent researchers and includes such topics as multirobot control, distributed robotic systems design, self-organizing systems, and sensing and navigation for cooperative robots. Distributed Autonomous Robotic Systems 2 is a valuable source for those whose work involves robotics and will be of great interest to those in the fields of artificial intelligence, self-organizing systems, artificial life, and computer science.
This volume of the SPAR series brings the proceedings of the fourteen edition of the DARS symposium on Distributed Autonomous Robotic Systems, whose proceedings have been published within SPAR since the past edition. This symposium took place in Boulder, CO from October 15th to 17th, 2018. The volume edited by Nikolaus Correll and Mac Schwager contains 36 scientific contributions cutting across planning, control, design, perception, networking, and optimization, all united through the common thread of distributed robotic systems.
This Special Issue reprint delves into the dynamic world of robotic systems, offering a comprehensive exploration of the latest advancements in modeling, optimization, and control. Robotics has emerged as a transformative field with applications spanning from industrial automation to healthcare and beyond. In this collection, leading researchers and practitioners present their cutting-edge work, shedding light on the intricate processes involved in designing, optimizing, and controlling robotic systems. From intricate mathematical models that capture the complex dynamics of robotic manipulators to innovative optimization techniques that enhance efficiency and performance, each contribution in this reprint offers valuable insights into the state-of-the-art methodologies shaping the future of robotics. The interdisciplinary nature of the field is highlighted, with discussions spanning areas such as mechanical design, electrical engineering, computer science, and artificial intelligence. Readers will find a diverse array of topics covered, including trajectory planning for autonomous vehicles, learning-based control strategies for humanoid robots, adaptive control algorithms for flexible manipulators, and many more. Through a blend of theoretical analysis, practical applications, and experimental validation, this reprint provides a comprehensive overview of the latest trends and challenges in the field of robotic systems.
Availability of a system is a crucial factor for planning and optimization. The concept is more challenging for modern systems such as robots and autonomous systems consisting of a complex configuration of components. As complex systems have become global and essential in today’s society, their reliable design and the determination of their availability have turned into a very important task for managers and engineers. Reliability Models of Complex Systems for Robots and Automation offers different models and approaches for reliability evaluation and optimization of a complex autonomous system. Comprehensive fault tree analysis on the critical components of industrial robots and its integration with the reliability block diagram approach is designed in order to investigate the robot system reliability. The cost and hazard decision tree are integrated for the first time in an approach to evaluate the reliability of a complex system. Considers a complex production system composing of several autonomous robots Develops binary state reliability evaluation model for a complex system Introduces new concepts of hazard decision tree Proposes fault tree and reliability block diagram for complex robotic systems Develops stochastic process based reliability evaluation and optimization models Today’s competitive world with increasing customer demands for highly reliable products makes reliability engineering a more challenging task. Reliability analysis is one of the main tools to ensure agreed delivery deadlines which in turn maintains certainty in real tangible factors such as customer goodwill and company reputation.
In this book, a generic model in as far as possible mathematical closed-formis developed that predicts the behavior of large self-organizing robot groups (robot swarms) based on their control algorithm. In addition, an extensive subsumption of the relatively young and distinctive interdisciplinary research field of swarm robotics is emphasized. The connection to many related fields is highlighted and the concepts and methods borrowed from these fields are described shortly.