Grasping an object in the scene with multiple unknown objects requires both the knowledge of which object to be the target and the planning of grasping pose. However, teleoperating a robot hand to find a proper grasping pose in an unstructured environment is often too complicated and time-consuming to perform. In this study, we propose an aided-grasping algorithm which autonomously corrects the pose of a robot hand using an eye-in-hand camera. We used multiple cameras for a natural vision-based teleoperation interface with an aided-grasping algorithm. Experiments with objects placed in arbitrary positions and angles have shown a successful implementation of the algorithm.