This book presents theoretical foundations and technical implementation guidelines for multi-vehicle fleet maneuvering, which can be implemented by readers and can also be a basis for future research. As a research monograph, this book presents fundamental concepts, theories, and technologies for localization, motion planning, and control of multi-vehicle systems, which can be a reference book for researchers and graduate students from different levels. As a technical guide, this book provides implementation guidelines, pseudocode, and flow diagrams for practitioners to develop their own...

This book aims at sharing knowledge about the technological opportunities and the main research challenges regarding robotics for logistics in supermarkets and retail stores, from the perspectives of the end-users, logistic companies, technology providers, and robotic researchers. The authors have been involved into the H2020 project Robotics Enabling Fully Integrated Logistics Lines for Supermarkets (REFILLS), aimed at improving logistics in supermarkets thanks to mobile robotic systems in close and smart collaboration with humans. The readers will find a comprehensive analysis of the...

This book introduces several appearance-based place recognition pipelines based on different mapping techniques for addressing loop-closure detection in mobile platforms with limited computational resources. The motivation behind this book has been the prospect that in many contemporary applications efficient methods are needed that can provide high performance under run-time and memory constraints. Thus, three different mapping techniques for addressing the task of place recognition for simultaneous localization and mapping (SLAM) are presented. The book at hand follows a tutorial-based...

One important robotics problem is “How can one program a robot to perform a task”? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating...

This book introduces a novel model-based dexterous manipulation framework, which, thanks to its precision and versatility, significantly advances the capabilities of robotic hands compared to the previous state of the art. This is achieved by combining a novel grasp state estimation algorithm, the first to integrate information from tactile sensing, proprioception and vision, with an impedance-based in-hand object controller, which enables leading manipulation capabilities, including finger gaiting. The developed concept is implemented on one of the most advanced robotic manipulators, the...

This book addresses the topic of autonomous flying robots physically interacting with the environment under the influence of wind. It aims to make aerial robots aware of the disturbance, interaction, and faults acting on them. This requires reasoning about the external wrench (force and torque) acting on the robot and distinguishing between wind, interactions, and collisions. The book takes a model-based approach and covers a systematic approach to parameter identification for flying robots. The book aims to provide a wind speed estimate independent of the external wrench, including...

This book explores cloud robotics by casting a light on key issues and proposing a novel approach towards implementation and practical aspects to allow for the widespread adoption of cloud-based functionality. The advent of cloud robotics can to unleash a new generation of smart robotic devices by allowing robots to explore cloud computing capabilities to share data and to offload heavy processing applications. Cloud robotics is investigated as an enabler to a series of applications and devices, questioning how the insertion of network and cloud technologies into such systems might affect...

One important robotics problem is “How can one program a robot to perform a task”? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating...

Using a designed vector field to guide robots to follow a given geometric desired path has found a range of practical applications, such as underwater pipeline inspection, warehouse navigation, and highway traffic monitoring. It is thus in great need to build a rigorous theory to guide practical implementations with formal guarantees. It is even so when multiple robots are required to follow predefined desired paths or maneuver on surfaces and coordinate their motions to efficiently accomplish repetitive and laborious tasks.