Adaptive Robotic Contour Following from Low Accuracy RGB-D Surface Profiling and Visual Servoing

2014 ◽  
Author(s):  
Danial Nakhaeinia ◽  
Pierre Payeur ◽  
Robert Laganiere
Keyword(s):  
Visual Servoing ◽  
Surface Profiling ◽  
Contour Following

Visual servoing in the task-function framework: A contour following task

1995 ◽  
Vol 12 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Eve Coste-Mani�re ◽  
Philippe Couvignou ◽  
Pradeep K. Khosla
Keyword(s):  
Visual Servoing ◽  
Contour Following

scholarly journals Dynamic performance improvement of direct image-based visual servoing in contour following

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775385 ◽  
Author(s):  
Che-Liang Li ◽  
Ming-Yang Cheng ◽  
Wei-Che Chang
Keyword(s):  
Visual Servoing ◽  
Sliding Mode ◽  
Industrial Robots ◽  
Image Feature ◽  
Interaction Matrix ◽  
Feedback Signal ◽  
Depth Information ◽  
Parametric Curve ◽  
Contour Following ◽  
Velocity Command

Image-based visual servoing (IBVS) has increasingly gained popularity and has been adopted in applications such as industrial robots, quadrotors, and unmanned aerial vehicles. When exploiting IBVS, the image feature velocity command obtained from the visual loop controller is converted to the velocity command of the workspace through the interaction matrix so as to converge image feature error. However, issues such as the noise/disturbance arising from image processing and the smoothness of image feature command are often overlooked in the design of the visual loop controller, especially in a contour following task. In particular, noise in the image feature will contaminate the image feedback signal so that the visual loop performance can be substantially affected. To cope with the aforementioned problem, this article employs the sliding mode controller to suppress the adverse effects caused by image feature noise. Moreover, by exploiting the idea of motion planning, a parametric curve interpolator is developed to generate smooth image feature commands. In addition, a depth observer is also designed to provide the depth information essential in the implementation of the interaction matrix. In order to assess the feasibility of the proposed approach, a two-degrees-of-freedom planar robot that employs an IBVS structure and an eye-to-hand camera configuration is used to conduct a contour following task. Contour following results verify the effectiveness of the proposed approach.

Experiments with a scanning tunneling microscope (STM) mounted in a scanning electron microscope (SEM)

1986 ◽  
Vol 44 ◽  
pp. 636-639
Author(s):  
Oliver C. Wells ◽  
Mark E. Welland
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Mechanical Stability ◽  
Tunneling Current ◽  
Feedback System ◽  
Scanning Tunneling ◽  
Surface Profiling ◽  
Close Proximity ◽  
Metal Tip ◽  
Scanning Electron

Scanning tunneling microscopes (STM) exist in two versions. In both of these, a pointed metal tip is scanned in close proximity to the specimen surface by means of three piezos. The distance of the tip from the sample is controlled by a feedback system to give a constant tunneling current between the tip and the sample. In the low-end STM, the system has a mechanical stability and a noise level to give a vertical resolution of between 0.1 nm and 1.0 nm. The atomic resolution STM can show individual atoms on the surface of the specimen.A low-end STM has been put into the specimen chamber of a scanning electron microscope (SEM). The first objective was to investigate technological problems such as surface profiling. The second objective was for exploratory studies. This second objective has already been achieved by showing that the STM can be used to study trapping sites in SiO2.

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