Becerra, H�ector . M.
Visual Control of Wheeled Mobile Robots Unifying Vision and Control in Generic Approaches / [electronic resource] : by H�ector . M Becerra, Carlos Sag�u�es. - XII, 118 p. 49 illus., 24 illus. in color. online resource. - Springer Tracts in Advanced Robotics, 103 1610-7438 ; . - Springer Tracts in Advanced Robotics, 103 .
Introduction -- Robust visual control based on the epipolar geometry -- A robust control scheme based on the trifocal tensor -- Dynamic pose-estimation for visual control -- Conclusions.
Vision-based control of wheeled mobile robots is an interesting field of research from a scientific and even social point of view due to its potential applicability. This book presents a formal treatment of some aspects of control theory applied to the problem of vision-based pose regulation of wheeled mobile robots. In this problem, the robot has to reach a desired position and orientation, which are specified by a target image. It is faced in such a way that vision and control are unified to achieve stability of the closed loop, a large region of convergence, without local minima, and good robustness against parametric uncertainty. Three different control schemes that rely on monocular vision as unique sensor are presented and evaluated experimentally. A common benefit of these approaches is that they are valid for imaging systems obeying approximately a central projection model, e.g., conventional cameras, catadioptric systems and some fisheye cameras. Thus, the presented control schemes are generic approaches. A minimum set of visual measurements, integrated in adequate task functions, are taken from a geometric constraint imposed between corresponding image features. Particularly, the epipolar geometry and the trifocal tensor are exploited since they can be used for generic scenes. A detailed experimental evaluation is presented for each control scheme.
9783319057835
10.1007/978-3-319-05783-5 doi
Engineering.
Artificial intelligence.
Image processing.
Control engineering.
Robotics.
Automation.
Engineering.
Robotics and Automation.
Artificial Intelligence (incl. Robotics).
Control.
Image Processing and Computer Vision.
TJ210.2-211.495 T59.5
629.892
Visual Control of Wheeled Mobile Robots Unifying Vision and Control in Generic Approaches / [electronic resource] : by H�ector . M Becerra, Carlos Sag�u�es. - XII, 118 p. 49 illus., 24 illus. in color. online resource. - Springer Tracts in Advanced Robotics, 103 1610-7438 ; . - Springer Tracts in Advanced Robotics, 103 .
Introduction -- Robust visual control based on the epipolar geometry -- A robust control scheme based on the trifocal tensor -- Dynamic pose-estimation for visual control -- Conclusions.
Vision-based control of wheeled mobile robots is an interesting field of research from a scientific and even social point of view due to its potential applicability. This book presents a formal treatment of some aspects of control theory applied to the problem of vision-based pose regulation of wheeled mobile robots. In this problem, the robot has to reach a desired position and orientation, which are specified by a target image. It is faced in such a way that vision and control are unified to achieve stability of the closed loop, a large region of convergence, without local minima, and good robustness against parametric uncertainty. Three different control schemes that rely on monocular vision as unique sensor are presented and evaluated experimentally. A common benefit of these approaches is that they are valid for imaging systems obeying approximately a central projection model, e.g., conventional cameras, catadioptric systems and some fisheye cameras. Thus, the presented control schemes are generic approaches. A minimum set of visual measurements, integrated in adequate task functions, are taken from a geometric constraint imposed between corresponding image features. Particularly, the epipolar geometry and the trifocal tensor are exploited since they can be used for generic scenes. A detailed experimental evaluation is presented for each control scheme.
9783319057835
10.1007/978-3-319-05783-5 doi
Engineering.
Artificial intelligence.
Image processing.
Control engineering.
Robotics.
Automation.
Engineering.
Robotics and Automation.
Artificial Intelligence (incl. Robotics).
Control.
Image Processing and Computer Vision.
TJ210.2-211.495 T59.5
629.892