Tactile sensing plays a crucial role to empower robotic hands with improved grasping and manipulating abilities. In this paper, we propose an anthropomorphic robotic hand design with dual air bag sensors integrated soft fingertips to achieve tactile sensing. The air bag sensor is low-cost, easy-to-build and deformable, and can be embedded in the fingertip, endows the hand with the ability to perceive and makes it have the mechanical complicance similar to the human fingertip. The air bag sensor exhibits high performance metrics, including a sensitivity of ~1.65 kPa/N, a minimum detection force of < 0.01 N, a response time of < 10 ms, and good stability and repeatability. The experimental results show that the proposed robotic hand performs well in surface texture detection, hard inclusion depth detection and object softness detection, as well as grasping tasks. By applying a machine learning algorithm to the experimental data, an accuracy of 0.767 and 0.898 was achieved in predicting hard inclusion depth and object hardness, respectively. This study provides a simple and effective tactile sensing solution for the design of anthropomorphic robotic hand, and may have possible applications such as end-effectors for humanoid robots or robotic palpation.

Soft robotic gloves can not only provide timely, effective, safe and cheap rehabilitation training for patients with impaired movement function of hand, but also assist in completing daily grasping activities. However, most soft robotic gloves are completely composed of flexible structures. Although they have high flexibility and safety, there are problems such as poor fit and low output force. In order to solve these problems, this paper refers to the structure of the human hand and designs an articulated rigid-soft hybrid robotic glove, which combines the advantages of rigid robotic gloves and soft robotic gloves, and has high flexibility, high output force and good fit. In addition, soft robotic gloves generally lack the ability to sense the force between the human hand and the glove. Therefore, this paper designed an array flexible force sensor, and studied the structure, signal acquisition and preparation process of the sensor. Finally, a complete test platform was built to test the performance of the rigid-soft hybrid robotic glove with force sensing function. The test results show that the robotic glove has good fit and high output force, can effectively assist training and assist grasping, and can perceive the contact force.

This work presents a humanoid soft robotics finger design with rigid skeletons and proprioceptive sensors. This 4-DOFs dexterous finger has soft joints and rigid phalanxes, which is about the size of human hand. To enhance the overall stiffness and for human-like behavior and configuration, rigid-soft actuators which we called quasi-joints are introduced. Although their lengths are shortened in this design, the soft actuators can still bend over 90°, exhibiting joint-like flexion and abduction/adduction. Thus interphalangeal joints (IPs) and metacarpophalangeal joint (MCP) are realized. EGaIn soft sensors are embedded into the structure for bending detection. In addition, multi-step molding fabrication method is introduced for this complex multi-material structure. This rigid-soft finger is a preliminary work and modular part of a highly dexterous humanoid soft robotic hand.