Recently the intelligent space applications have become increasingly beneficial considering robot control. In this paper the visual controlling concept is presented in the iSpace framework. The positions of the end-effector of the robot manipulator are presented by the 3D spatial coordinates extracted from image pairs. The exact image Jacobian matrix of the mapping from Cartesian space to image space is given, the task space controllers can be directly extended to image-space controllers. The Jacobian matrix poses uncertainty if modeling and calibration errors are present. Despite the fact that much progress has been presented in the literature of visual servoing, there are only a few results obtained for the stability analysis in presence of the uncertain camera parameters. This research aims developing a new method for the control of the manipulator in Cartesian space, using the vision information of the environment obtained by cameras using the OptiTrack framework. The robotic manipulator is mounted on a mobile tank. The control scheme allows the end effector to transit smoothly from Cartesian-space feedback to vision-space feedback when the target is inside the vicinity of the camera. Key points on the manipulator are marked which are detected by the camera system. The framework calculates the coordinates of the markers, and thus estimate the state of each joint of the manipulator within a margin of error. In order to achieve the most precise estimation each camera image is weighted during the evaluation. The weights are determined using data set of images. After, a likelihood function is assigned for each joint that is used for defining the position and designing the motion. During the experiments the proposed control concept has proven to be reliable.