# Design of an Eye-in-Hand Smart Gripper for Visual and Mechanical Adaptation in Grasping
## 1 Introduction
The difference between the eye-on-hand and the eye-in-hand configurations is primarily on the camera's mounting position. In eye-in-hand configuration, the camera shares the same coordinate system with the gripper. In eye-on-hand configuration, the camera and the gripper are located and described by different coordinates in which configuration of the so-called out-sight problem may occur when the camera is close to the object. This problem is graphically illustrated in Figure 2, where the size of the target object is set as a ten-by-ten-centimeter square, and the offset between eye-in-hand and eye-on-hand  
Figure 1: Relationship between the camera and gripper in different configurations. coordinate is 15 cm. As the distance between the camera and the target object changes, in particular when the distance is less than 30 cm, the target object becomes out of view in eye-on-hand configuration. Nevertheless, such a problem does not occur in the eye-in-hand configuration, as it is still available regardless of the relative position and distance between the camera and the gripper. In [PERSON]'s paper, the main purpose was to find a crop-like berry, which was behind some leaves, and collected by a robot arm with a camera on the manipulator [9]. The camera can avoid the leaves and find the crop by moving the manipulator using an eye-on-hand system. In addition to [PERSON]'s paper, a substantial number of research studies have used the eye-on-hand configuration to avoid occlusion [10; 11; 12; 13]. In fact, both eye-in-hand and eye-on-hand configurations can perform intuitive teleoperation tasks using high-DOF servo-manipulators [14]. The camera can obtain images from different angles by controlling the robot because it is mounted at the end of the manipulator for easier calibration of both the camera and manipulator [15; 16; 17]. Furthermore, should the RGB-D camera be combined with eye-on-hand configuration, calculation of the proper gripping position by the depth gradient feature without different camera shots becomes simple [18]. The primary difference between the eye-on-hand and eye-in-hand configurations is that the coordinates of the camera contain an offset with the center of the gripper in the eye-on-hand system. For the eye-on-hand system, when the gripper approaches the target, the camera is blocked by obstacles or the gripper itself and loses the target while tracking the moving target. In addition, occlusion by the gripper itself can be easily avoided with the eye-in-hand setup, and the eye-in-hand setup is simply calibrated because it is not offset from the gripper's coordinate system. In this paper, the eye-in-hand configuration was applied in the model robotic gripper in which the controller of the gripper and the visual calculator were integrated inside the gripper, allowing the gripper to become a plug-and-play module. In addition to the mechanical adaptivity, this eye-in-hand gripper also possessed features, namely visual adaptivity, by its shape recognize feature for different target objects and visual servoing feature for tracking a moving object, respectively. The sectional view of the gripper is shown in Figure 3. This adaptive gripper contained three main motors for the motion of the three fingers, and two side motors for the finger's spread angle, each of which operated independently and was controlled by a Raspberry PI computer. The adaptive finger in this gripper was designed with multiple degrees of freedom, but only driven by a single motor, which made the finger have redundant degrees of freedom. The calculation and kinematics of the linkage structure are as follows. Figure 2: The out-sight problem of the eye-on-hand system with a 10 mm \(\times\) 10 mm target.