TY  - BOOK
AU  - Yu,Junzhi
AU  - Chen,Xingyu
AU  - Kong,Shihan
TI  - Visual perception and control of underwater robots
SN  - 9781000346596
AV  - TC1662 .Y834 2021
U1  - 623.82/05 23
PY  - 2021///
CY  - Boca Raton, FL
PB  - CRC Press
KW  - Remote submersibles
KW  - Robots
KW  - Control systems
KW  - Robot vision
KW  - COMPUTERS / Computer Graphics / General
KW  - bisacsh
KW  - TECHNOLOGY / General
KW  - TECHNOLOGY / Engineering / General
N2  - "This book 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 sea. The other one 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. Meanwhile, the mainstream technologies that are 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 the book"--
UR  - https://www.taylorfrancis.com/books/9781003144281
UR  - http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
ER  -