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Image-Based Visual Servoing for Robotic Systems: A Nonlinear Lyapunov-Based Control Approach.

DE2005835391

Publication Date	2004
Page Count	8
Abstract	The objective of this project is to enable current and future EM robots with an increased ability to perceive and interact with unstructured and unknown environments through the use of camera-based visual servo controlled robots. The scientific goals of this research are to develop a new visual servo control methodology that: (1) adapts for the unknown camera calibration parameters (e.g., focal length, scaling factors, camera position and orientation) and the physical parameters of the robotic system (e.g., mass, inertia, friction), (2) compensates for unknown depth information (extract 3D information from the 2D image), and (3) enables multi-uncalibrated cameras to be used as a means to provide a larger field-of-view. Nonlinear Lyapunov-based techniques are being used to overcome the complex control issues and alleviate many of the restrictive assumptions that impact current visual servo controlled robotic systems.
Keywords	Image processing Computer vision Robots Accuracy Calibration Cameras Friction Lyapunov functions Orientation Productivity
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200520

Image-Based Visual Servoing for Robotic Systems: A Nonlinear Lyapunov-Based Control Approach.

Image-Based Visual Servoing for Robotic Systems: A Nonlinear Lyapunov-Based Control Approach.
DE2005835391

Publication Date	2004
Page Count	8
Abstract	The objective of this project is to enable current and future EM robots with an increased ability to perceive and interact with unstructured and unknown environments through the use of camera-based visual servo controlled robots. The scientific goals of this research are to develop a new visual servo control methodology that: (1) adapts for the unknown camera calibration parameters (e.g., focal length, scaling factors, camera position and orientation) and the physical parameters of the robotic system (e.g., mass, inertia, friction), (2) compensates for unknown depth information (extract 3D information from the 2D image), and (3) enables multi-uncalibrated cameras to be used as a means to provide a larger field-of-view. Nonlinear Lyapunov-based techniques are being used to overcome the complex control issues and alleviate many of the restrictive assumptions that impact current visual servo controlled robotic systems.
Keywords	Image processing Computer vision Robots Accuracy Calibration Cameras Friction Lyapunov functions Orientation Productivity
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200520