Robotic hands perform several amazing functions similar to the human hands, thereby offering high flexibility in terms of the tasks performed. However, developing integrated hands without additional actuation parts while maintaining important functions such as human-level dexterity and grasping force is challenging. The actuation parts make it difficult to integrate these hands into existing robotic arms, thus limiting their applicability. Based on a linkage-driven mechanism, an integrated linkage-driven dexterous anthropomorphic robotic hand called ILDA hand, which integrates all the components required for actuation and sensing and possesses high dexterity, is developed. It has the following features: 15-degree-of-freedom (20 joints), a fingertip force of 34N, compact size (maximum length: 218 mm) without additional parts, low weight of 1.1 kg, and tactile sensing capabilities. Actual manipulation tasks involving tools used in everyday life are performed with the hand mounted on a commercial robot arm.

The robotic gripper is an essential component for handling, manipulating, and transporting objects. However, the parallel rigid gripper, which is one of the most widely used grippers in robotics, has limitations in handling fragile objects with a proper gripping force. We present a shape-adaptive universal soft gripper that can grip complex-shaped fragile objects with a high holding force. The shape-adaptive skin of the gripper has extremely low stiffness ( ~ 46 kPa), even lower than that of tofu ( ~ 57 kPa); hence, it can inherently prevent damage to the object. In addition, only the area pressed by the object is selectively deformed, so the contact surface of the gripper can be deformed to match the target object contour. A stiffness transition in the gripper from a soft to hard state follows to achieve effective holding of the object, not just weak object hanging as the previous soft gripper. These characteristics are enabled by a sheet-shaped shape retention layer, a honeycomb-shaped soft supporting layer, and a four-sided wall structure to increase shear modulus. We present applications to show the performance of the gripper, including gripping tofu, preparing a cocktail with a squeezed lemon, and whole chicken soup.

To manipulate objects using a robot hand, it is important to measure the information of the various forces on the fingertips. In this letter, a six-axis force/torque (F/T) fingertip sensor for a robot hand is introduced. The sensor was developed to provide the ability to measure six-axis F/T while remaining feasible for robot fingertip integration because of its miniaturization, light weight, and low cost (thanks to its simple manufacturing process). In particular, a novel highly sensitive shear force measurement method is proposed that uses the eccentricity of two cylinders. The designed six-axis F/T sensor was also fabricated. We demonstrate that the developed sensor can be easily installed into the human-sized fingertip of a robot, and we performed an accuracy evaluation using several experiments.

Force/Torque (F/T) sensing technology enables a dexterous robot control such as direct teaching, master-slave system, and pick-and-place task. In general, 6-axis F/T sensor is attached to the end-effector of the robot manipulator to assist in utilizing advanced robot systems. However, in actual applications, various tools such as robotic grippers, robotic hand, grinders are attached to the sensor and it causes F/T offset} with respect to the gravity. In this letter, Autonomous Weight Compensating(AWC) technique for 6-axis F/T sensor is presented. The proposed AWC technique can reduce the F/T offsets by estimating the F/T offsets through installed Inertial Measurement Unit(IMU) sensor. In this study, the 6-axis F/T are measured based on capacitance sensing scheme and to estimate the orientation of the sensor, a 9-axis IMU sensor is installed inside of the sensor. Then, the F/T offsets are calibrated via Artificial Neural Network(ANN) model. As a result, the sensor can reduce the F/T offsets without any additional computing time in robot operating period. Finally, the performance of the proposed method is demonstrated through comparing the F/T data with both trained data and untrained data.

Robotic manipulators require contact force sensing capabilities to sense the contact force between the manipulator and an object. Specifically, for humans and robots to coexist in the work environment, the robot must be able to detect an external force applied by a human. This study presents a new intrinsic force sensing method for robot manipulators that can obtain accurate information of the external force applied by a human during human–robot interaction. The method employs a robot cover, which is typically utilized in robot manipulators. Unlike conventional force sensing methods, a six-axis force/torque sensor is placed between the cover and the link of the robot manipulator. As a result, the proposed method provides information of the three-axis contact force applied to the cover surface and its contact location. Therefore, the cover itself becomes a sensorized cover based on the intrinsic force sensing method. To evaluate its sensing performance, the sensorized cover is experimentally validated using reference sensors. Finally, an experiment is performed in which the robot successfully recognizes letters written on the cover, indicating a high level of contact force sensing performance.

Astrictive-type grippers, which generate gripping forces from adhesive forces at the contact surface, such as suction cup, are popular end-effectors as picking solutions because of their simplicity and small working space. However, the adhesive force of the astrictive gripper decreases with increasing complexity of the object surface; thus, its application has been restricted to simple picking of objects with a flat surface. Here, in this article, we present an all-round honeycomb astrictive gripper that has an orthotropic surface tension for grasping highly irregular shaped objects with an uneven surface. The design is inspired by mimicking the two-level (macro- and mesoscale) shape adaptation of the octopus's leg. The stiffness-variable structure is also consisted to change its stiffness similar to the function of octopus's leg, and owing to the combination of these structures makes possible to perform various tasks, including hammering, breakfast serving, and vaccination, which were not possible for previous astrictive gripper.