- A simple gripper for a robotic arm capable of grasping various objects in manufacturing lines provides great benefits in terms of standardization of grippers, reducing engineering time and costs. This will provide the possibility to reuse the manufacturing line for several products of different geometry without significant changes. The goal is to make a gripper such that it will be a commodity similar to the robot arms. The algorithm, termed 3D-OCOG (3-Dimensional Objects COmmon Grasp search) and proposed in this paper, searches for a common grasp configuration over a set of spatial objects. It maps all possible grasps for each object that satisfy force closure and quality criteria so the grasps could counter-balance external wrenches (forces and torque) applied to the object. The mapped grasps are parameterized as feature vectors in a high-dimensional space. This feature vector describes the design of the gripper. A database of feature vectors is generated for all possible grasps for each object in the feature space. A similarity join based on nearest-neighbor search and classification algorithm are used for intersecting all possible feature vectors over all objects and finding common ones. Each feature vector found is a grasp configuration for the group of objects, which directly implies the gripper design. Simulations of a 3-finger grasp of four meshed objects resulted in several common grasp solutions. Therefore, a designated experimental setup was established composed of three robotic fingers, to simulate the grasp of the test objects. Results of the simulations and experiments validate the feasibility of the proposed algorithm.