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This paper aims to design a novel jaw gripper with human-sized anthropomorphic features to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. The growing demand from traditional high-mix low-volume and new massive customized manufacturing industry requires the robot with configurability and flexibility. In the electronic manufacturing industry particularly, the design of the robotic hand with sufficient dexterity and configuration is important for the robot to accomplish the assembly task reliably and robustly. It is important for the robot to be able to grasp and manipulate a large number of assembly parts or tools.

In this research, a novel jaw-like gripper with human-sized anthropomorphic features is designed for online in-hand precise positioning and twisting. It retains the simplicity feature of traditional industrial grippers and dexterity features of dexterous robotic hands.

The gripper is able to apply suitable gripping force on assembly parts and performs reliable twisting movement within limited time to meet the industrial requirements. Manipulating several cylindrical assembly parts by robot, as an experimental case in this paper, is studied to evaluate its performance. The effectiveness of proposed gripper design and mechanical analysis is proved by the simulation and experimental results.

The main originality of this research is that a novel jaw gripper with human-sized anthropomorphic features is designed to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. With this gripper, the robotic system will be sufficiently flexible to deal with various assembly tasks.

Hand gesture-based interaction can provide far more intuitive, natural and immersive feelings for users to manipulate 3D objects for virtual assembly (VA). A mechanical assembly consists of mostly general-purpose machine elements or mechanical parts that can be defined into four types based on their geometric features and functionalities. For different types of machine elements, engineers formulate corresponding grasping gestures based on their domain knowledge or customs for ease of assembly. Therefore, this paper aims to support a virtual hand to assemble mechanical parts.

It proposes a novel glove-based virtual hand grasping approach for virtual mechanical assembly. The kinematic model of virtual hand is set up first by analyzing the hand structure and possible movements, and then four types of grasping gestures are defined with joint angles of fingers for connectors and three types of parts, respectively. The recognition of virtual hand grasping is developed based on collision detection and gesture matching. Moreover, stable grasping conditions are discussed.

A prototype system is designed and developed to implement the proposed approach. The case study on VA of a two-stage gear reducer demonstrates the functionality of the system. From the users’ feedback, it is found that more natural and stable hand grasping interaction for VA of mechanical parts can be achieved.

It proposes a novel glove-based virtual hand grasping approach for virtual mechanical assembly.