Visual Perception and Control of Underwater Robots covers theories and applications from aquatic visual perception and underwater robotics. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed. More specifically, the book includes adversarial critic learning for visual restoration, NSGA-II-based calibration for binocular measurement, prior knowledge refinement for object detection, analysis of temporal detection performance, as well as the effect of the aquatic data domain on object detection. With the aid of visual perception technologies, two up-to-date underwater robot systems are demonstrated. The first system focuses on underwater robotic operation for the task of object collection in the sea. The second is an untethered biomimetic robotic fish with a camera stabilizer, its control methods based on visual tracking. The authors provide a self-contained and comprehensive guide to understand underwater visual perception and control. Bridging the gap between theory and practice in underwater vision, the book features implementable algorithms, numerical examples, and tests, where codes are publicly available. Additionally, the mainstream technologies covered in the book include deep learning, adversarial learning, evolutionary computation, robust control, and underwater bionics. Researchers, senior undergraduate and graduate students, and engineers dealing with underwater visual perception and control will benefit from this work.

Visual Perception and Control of Underwater Robots covers theories and applications from aquatic visual perception and underwater robotics. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed. More specifically, the book includes adversarial critic learning for visual restoration, NSGA-II-based calibration for binocular measurement, prior knowledge refinement for object detection, analysis of temporal detection performance, as well as the effect of the aquatic data domain on object detection. With the aid of visual perception technologies, two up-to-date underwater robot systems are demonstrated. The first system focuses on underwater robotic operation for the task of object collection in the sea. The second is an untethered biomimetic robotic fish with a camera stabilizer, its control methods based on visual tracking. The authors provide a self-contained and comprehensive guide to understand underwater visual perception and control. Bridging the gap between theory and practice in underwater vision, the book features implementable algorithms, numerical examples, and tests, where codes are publicly available. Additionally, the mainstream technologies covered in the book include deep learning, adversarial learning, evolutionary computation, robust control, and underwater bionics. Researchers, senior undergraduate and graduate students, and engineers dealing with underwater visual perception and control will benefit from this work.

This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP.

This book moves toward the realization of domestic robots by presenting an integrated view of computer vision and robotics, covering fundamental topics including optimal sensor design, visual servo-ing, 3D object modelling and recognition, and multi-cue tracking, emphasizing robustness throughout. Covering theory and implementation, experimental results and comprehensive multimedia support including video clips, VRML data, C++ code and lecture slides, this book is a practical reference for roboticists and a valuable teaching resource.

Underwater robots play a significant role in ocean exploration. This book provides full coverage of the theoretical and practical aspects of bionic gliding underwater robots, including system design, modeling control, and motion planning. To overcome the inherent shortcomings of traditional underwater robots that can simultaneously lack maneuverability and endurance, a new type of robot, the bionic gliding underwater robot, has attracted much attention from scientists and engineers. On the one hand, by imitating the appearance and swimming mechanisms of natural creatures, bionic gliding underwater robots achieve high maneuverability, swimming efficiency, and strong concealment. On the other hand, borrowing from the buoyancy adjustment systems of underwater gliders, bionic gliding underwater robots can obtain strong endurance, which is significant in practical applications. Taking gliding robotic dolphin and fish as examples, the designed prototypes and proposed methods are discussed, offering valuable insights into the development of next-generation underwater robots that are well suited for various oceanic applications. This book will be of great interest to students and professionals alike in the field of robotics or intelligent control. It will also be a great reference for engineers or technicians who deal with the development of underwater robots.

This book constitutes the proceedings of the 13th International Conference on Intelligent Robotics and Applications, ICIRA 2020, held in Kuala Lumpur, Malaysia, in November 2020. The 45 full papers and 3 short papers were carefully reviewed and selected from 66 submissions. The accepted papers were grouped into various subtopics including Advanced Measurement and Machine Vision System; Automation; Human-Robot Interaction; Mobile Robots and Intelligent Autonomous System; Recent Trends in Computational Intelligence; Robot Design, and Development and Control. Due to the Corona pandemic ICIRA 2020 was held as a virtual event.

This book is a comprehensive collection and practical guide on robotics derived from the author's research in robotics since 1988. The Chinese edition of this book has sold over 300,000 copies, and is one of the best-selling books on robotics in China.The book covers the core technology of robotics, including the basic theories and techniques of robot manipulator, mobile robots to focus on location navigation, and intelligent control underpinned by artificial intelligence and deep learning. Several case studies from national research projects in China are also included to help readers understand the theoretical foundations of robotics and related application developments. This book is a valuable reference for undergraduate and graduate students of robotics courses.

This book constitutes the refereed proceedings of the 7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCII 2019, in Orlando, Florida, USA, in July 2019. A total of 1274 papers and 209 posters have been accepted for publication in the HCII 2019 proceedings from a total of 5029 submissions. The 36 papers included in this volume were organized in topical sections on IoT and big data; smart cities and built environments; perception and emotion in DAPI; and DAPI for health and learning.

This volume constitutes the refereed proceedings of the 11th International Conference on Simulation and Adaptive Behavior, SAB 2010, held in Paris and Clos Lucé, France, in August 2010. The articles cover all main areas in animat research, including perception and motor control, action selection, motivation and emotion, internal models and representation, collective behavior, language evolution, evolution and learning. The authors focus on well-defined models, computer simulations or robotic models, that help to characterize and compare various organizational principles, architectures, and adaptation processes capable of inducing adaptive behavior in real animals or synthetic agents, the animats.