In this work, we present different eye-in-hand visual servoing control schemes applied to a robotic harvesting task of soft fruits in the presence of parametric uncertainties in the system models. The first scheme combines position-based visual servoing (PBVS) and image-based visual servoing (IBVS) approaches in order to perform respectively an approach phase to the fruit and then a fine tuning of the end-effector to harvest. The second scheme uses a hybrid visual servoing (HVS) approach to fulfill the complete harvesting task, by designing a suitable control law which combines error vectors defined in both the image and operational spaces. For detecting the fruits, an algorithm based on the combination of the OHTA color space and Otsu’s threshold method for a fast recognition of mature fruits in complex scenarios. In addition, a more accurate detection method employs a pre-trained deep encoder-decoder algorithm based on a minimized Segnet version for a fast and cheap inference during the task execution. The object localization is accomplished by employing an image triangulation technique, which combines the speeded-up-robust-features (SURF) and the-randomsample-consensus (RANSAC) or the Oriented FAST and Rotated BRIEF and the Brute-Force Matcher (BF-Matcher) algorithms to extract the fruit image feature and match it to its correspondent feature-point into the other view of the stereo camera. However, since these algorithms are computationally expensive for the task requirements, a faster estimation method uses the fruit centroid and a homogeneous transformation for discovering matching points. Finally, a vision-based sliding-mode-control scheme and a switching monitoring function are employed to cope with uncertainties in the calibration parameters of the camera-robot system. In this context, it is possible to guarantee the asymptotic stability and convergence of the image feature error, even if the misalignment angle, around the z-axis, between the camera and end-effector frames is uncertain. 3D computer simulations and preliminary experimental results, obtained with a Mitsubishi robot arm RV-2AJ carrying out a simple strawberry picking task, are included to illustrate the performance and effectiveness of the proposed control scheme.