Integrated linkage-driven dexterous anthropomorphic robotic hand.

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.

Estimation and Control of Cooperative Aerial Manipulators for a Payload with an Arbitrary Center-of-Mass.

This paper presents an integrated framework that integrates the kinematic and dynamic parameter estimation of an irregular object with non-uniform mass distribution for cooperative aerial manipulators. Unlike existing approaches, including impedance-based control which requires expensive force/torque sensors or the first-order-momentum-based estimator which is weak to noise, this paper suggests a method without such sensor and strong to noise by exploiting the decentralized dynamics and sliding-mode-momentum observer. First, the kinematic estimator estimates the relative distances of multiple aerial manipulators by using translational and angular velocities between aerial robots. By exploiting the distance estimation, the desired trajectories for each aerial manipulator are set. Second, the dynamic parameter estimation is performed for the mass of the common object and the vector between the end-effector frame and the center of mass of the object. Finally, the proposed framework is validated with simulations using aerial manipulators combined with two degrees-of-freedom robotic arms using a noisy measurement. Throughout the simulation, we can decrease the mass estimation error by 60% compared to the existing first-order momentum-based method. In addition, a comparison study shows that the proposed method satisfactorily estimates an arbitrary center-of-mass of an unknown payload in noisy environments.

Rugged and Compact Three-Axis Force/Torque Sensor for Wearable Robots.

In the field of robotics, sensors are crucial in enabling the interaction between robots and their users. To ensure this interaction, sensors mainly measure the user's strength, and based on this, wearable robots are controlled. In this paper, we propose a novel three-axis force/torque sensor for wearable robots that is compact and has a high load capacity. The bolt and nut combination of the proposed sensor is designed to measure high-load weights, and the simple structure of this combination allows the sensor to be compact and light. Additionally, to measure the three-axis force/torque, we design three capacitance-sensing cells. These cells are arranged in parallel to measure the difference in capacitance between the positive and negative electrodes. From the capacitance change measured by these sensing cells, force/torque information is converted through deep neural network calibration. The sensing point can also be confirmed using the geometric and kinematic relation of the sensor. The proposed sensor is manufactured through a simple and inexpensive process using cheap and simply structured components. The performance of the sensor, such as its repeatability and capacity, is evaluated using several experimental setups. In addition, the sensor is applied to a wearable robot to measure the force of an artificial muscle.

Shape Estimation of Soft Manipulator Using Stretchable Sensor.

The soft robot manipulator is attracting attention in the surgical fields with its intrinsic softness, lightness in its weight, and safety toward the human organ. However, it cannot be used widely because of its difficulty of control. To control a soft robot manipulator accurately, shape sensing is essential. This paper presents a method of estimating the shape of a soft robot manipulator by using a skin-type stretchable sensor composed of a multiwalled carbon nanotube (MWCNT) and silicone (p7670). The sensor can be easily fabricated and applied by simply attaching it to the surface of the soft manipulator. In its fabrication, MWCNT is sprayed on a teflon sheet, and liquid-state silicone is poured on it. After curing, we turn it over and cover it with another silicone layer. The sensor is fabricated with a sandwich structure to decrease the hysteresis of the sensor. After calibration and determining the relationship between the resistance of the sensor and the strain, three sensors are attached at 120° intervals. Using the obtained data, the curvature of the manipulator is calculated, and the entire shape is reconstructed. To validate its accuracy, the estimated shape is compared with the camera data. We experiment with three, six, and nine sensors attached, and the result of the error of shape estimation is compared. As a result, the minimum tip position error is approximately 8.9 mm, which corresponded to 4.45% of the total length of the manipulator when using nine sensors.

A Novel Fabric Muscle Based on Shape Memory Alloy Springs.

Fabric muscle is important for wearable robots that are soft, compliant, and silent with high contractility and high force. This study presents a novel shape memory alloy (SMA) spring-based fabric muscle (SFM). The SFM is manufactured by bundling SMA springs with proven performance as artificial muscle. The SFM generates high contractility and high force, and is soft, flexible, and light because it is covered with fabric used to make actual clothes. The SFM is contracted by heat and shows a contraction strain of 50% at a heating temperature of 70°C while generating 100 N force or higher. Furthermore, it generates a maximum contraction strain of 67% under no load. To drive it with the optimum voltage and current, the SFM is designed by optimizing the serial and parallel connection methods for the embedded SMA springs. We propose herein design and manufacturing methods for the SFM and verify the usability of the SFM as a soft actuator through a performance evaluation. The SFM as a soft actuator with a simple structure-like fabric is easily applicable to soft wearable robots that can support muscle power by simply being attached to usual suits. The SFM has a soft touch, and is lightweight; hence, it has the potential for wide applications to new-concept soft wearable robots that can be comfortably worn anytime and anywhere like usual clothes.

Human-mimetic soft robot joint for shock absorption through joint dislocation.

This paper presents a human-mimetic manipulator capable of shock absorption by using dislocation at the soft joint. A one degree-of-freedom (DOF) soft robot joint was developed based on the human elbow-joint structure, especially mimicking the humeroulnar joint in the elbow. Each component of the soft joint is combined by an elastic ligament, which is made up of elastic rubber and is attached to the pivot joint pin positioned at a predetermined place according to a specially designed pin guide. As an external impact is applied to the joint, the elastic ligament is elongated as the pivot joint pin is moved from the predetermined place. This state is defined as a dislocation, which is similar to the dislocation of a human joint when impacted. Dislocation in the proposed soft robot joint occurred when the external impact was larger than the predetermined threshold force. This threshold force can be predicted by the modulus of the elastic ligament and the shape of the pin guide, and the theoretical model was developed in this study. To evaluate the function of dislocation, dynamic and quasi-static impact tests were performed at the 1-DOF soft robot joint. Moreover, the human-mimetic manipulator is proposed based on the 2-DOF soft robot joint. This manipulator can realize four motions of a human arm using the pneumatic artificial muscles: flexion, extension, pronation and supination. Each artificial muscle and bone structure were similar to the human arm structure, and thus the configuration of each bone structure of the manipulator for each motion is similar to the configurations of a human skeletal structure. This manipulator was also capable of dislocation to absorb the external impact. The developed human-mimetic manipulator with a soft joint is expected to be applied to a naturally safe humanoid robot that works with humans in the same space.

A transparent and stretchable graphene-based actuator for tactile display.

A tactile display is an important tool to help humans interact with machines by using touch. In this paper, we present a transparent and stretchable graphene-based actuator for advanced tactile displays. The proposed actuator is composed of transparent and compliant graphene electrodes and a dielectric elastomer substrate. Since the electrode is coated onto the appointed region of the substrate layer by layer, only the area of the dielectric elastomer substrate with electrodes bumps up in response to the input voltage, which consequently produces actuation. The actuator is proven to be operable while preserving its electrical and mechanical properties even under 25% stretching. Also, the simple fabrication of the proposed actuator is cost-effective and can easily be extended to multiple arrays. The actuator is expected to be applicable to various applications including tactile displays, vari-focal lenses etc.