الفهرس | Only 14 pages are availabe for public view |
Abstract Among all sensors, vision is the most complementary one with respect to the sensory information it provides to be included in the control loop since visual sensors are powerful means for a robot to perceive its environment. In particular, the use of visual feedback from sensor camera, when used in a correct manner, guarantees accurate positioning, robustness to calibration uncertainties, and reactivity to environmental changes. Visual servoing is a viable method for robotic control based on the utilization of visual information extracted from images to close the robot control loop. Visual information obtained from the image processing can be used to extracting 2D features. It can also be used to estimating pose parameters by employing a pose estimation algorithm from computer vision. The estimated pose is transformed into the 3D features. These 2D and/or 3D features are then used in the control scheme. Usually, in an open control scheme it is not that important to study arm robot singularity as the path can be adjusted as needed but in visual servoing application which is considered a closed control scheme, it is very important to study arm singularities to be able to avoid them or control the arm around these positions. The purpose is to optimize the behavior of the visual servoing control system to avoid any singular conguration |