Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: - Introduces several new contributions to the representation and management of humans in autonomous robotic systems; - Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; - Engages with the potential repercussions of cognitive computing and HRI in the real world. - Introduces several new contributions to the representation and management of humans in an autonomous robotic system - Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society - Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
"Advances in Human-Robot Interaction" provides a unique collection of recent research in human-robot interaction. It covers the basic important research areas ranging from multi-modal interfaces, interpretation, interaction, learning, or motion coordination to topics such as physical interaction, systems, and architectures. The book addresses key issues of human-robot interaction concerned with perception, modelling, control, planning and cognition, covering a wide spectrum of applications. This includes interaction and communication with robots in manufacturing environments and the collaboration and co-existence with assistive robots in domestic environments. Among the presented examples are a robotic bartender, a new programming paradigm for a cleaning robot, or an approach to interactive teaching of a robot assistant in manufacturing environment. This carefully edited book reports on contributions from leading German academic institutions and industrial companies brought together within MORPHA, a 4 year project on interaction and communication between humans and anthropomorphic robot assistants.
Opto-mechatronics-the fusion of optical and mechatronic technologies-has been integral in the evolution of machines, systems, and products that are smaller and more precise, more intelligent, and more autonomous. For the technology to reach its full potential, however, engineers and researchers from many disciplines must learn to work together thro
Soldier-robot teams will be an important component of future battle spaces, creating a complex but potentially more survivable and effective combat force. The complexity of the battlefield of the future presents its own problems. The variety of robotic systems and the almost infinite number of possible military missions create a dilemma for researchers who wish to predict human-robot interactions (HRI) performance in future environments. Human-Robot Interactions in Future Military Operations provides an opportunity for scientists investigating military issues related to HRI to present their results cohesively within a single volume. The issues range from operators interacting with small ground robots and aerial vehicles to supervising large, near-autonomous vehicles capable of intelligent battlefield behaviors. The ability of the human to 'team' with intelligent unmanned systems in such environments is the focus of the volume. As such, chapters are written by recognized leaders within their disciplines and they discuss their research in the context of a broad-based approach. Therefore the book allows researchers from differing disciplines to be brought up to date on both theoretical and methodological issues surrounding human-robot interaction in military environments. The overall objective of this volume is to illuminate the challenges and potential solutions for military HRI through discussion of the many approaches that have been utilized in order to converge on a better understanding of this relatively complex concept. It should be noted that many of these issues will generalize to civilian applications as robotic technology matures. An important outcome is the focus on developing general human-robot teaming principles and guidelines to help both the human factors design and training community develop a better understanding of this nascent but revolutionary technology. Much of the research within the book is based on the Human Research and Engineering Directorate (HRED), U.S. Army Research Laboratory (ARL) 5-year Army Technology Objective (ATO) research program. The program addressed HRI and teaming for both aerial and ground robotic assets in conjunction with the U.S. Army Tank and Automotive Research and Development Center (TARDEC) and the Aviation and Missile Development Center (AMRDEC) The purpose of the program was to understand HRI issues in order to develop and evaluate technologies to improve HRI battlefield performance for Future Combat Systems (FCS). The work within this volume goes beyond the research results to encapsulate the ATO's findings and discuss them in a broader context in order to understand both their military and civilian implications. For this reason, scientists conducting related research have contributed additional chapters to widen the scope of the original research boundaries.
Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis