For safe coexistence between robots and humans, it is important for robots to detect the presence of nearby humans as well as any physical contacts made to its body. The design of a modular textile ...sensor array and an algorithm for multi‐modal sensing of human touches and other contacts with their contact forces proposed. Each sensor module in the array is capable of multi‐modal sensing, and the entire array with multiple modules requires only two wires to read the outputs from all the modules using band‐stop filter circuits. The proposed sensor system shows the structural modularity, achieved by simple fabrication of sequential lamination of conductive and non‐conductive textile materials, realizing electrical connections through conductive snap buttons that connect the modules to the circuit. The functional modularity is also achieved through the compensation algorithm, derived from the analysis of the transfer function in the frequency domain. The algorithm significantly reduces signal interferences between modules. The multi‐modality, the textile‐based design, and the structural and functional modularity of the proposed system enable practical applications to various robotic systems, including robotic skin for a collaborative robot, a wearable sensor, a robot hand sensor, and a human–computer interface, as demonstrated in this study.
For safe coexistence between humans and robots, a modular textile sensor system is proposed. This system allows multi‐modal sensing of human touches and physical contacts. The proposed sensor system requires only two signal wires even though the number of sensor modules increases, which is enabled by a sensing algorithm that significantly reduces signal interferences between modules.
Despite the great advancement in designing diverse soft robots, they are not yet as dexterous as animals in many aspects. One challenge is that they still lack the compact design of an artificial ...motor unit with a great comprehensive performance that can be conveniently fabricated, although many recently developed artificial muscles have shown excellent properties in one or two aspects. Herein, an artificial motor unit is developed based on gold‐coated ultrathin liquid crystal elastomer (LCE) film. Subject to a voltage, Joule heating generated by the gold film increases the temperature of the LCE film underneath and causes it to contract. Due to the small thermal inertial and electrically controlling method of the ultrathin LCE structure, its cyclic actuation speed is fast and controllable. It is shown that under electrical stimulation, the actuation strain of the LCE‐based motor unit reaches 45%, the strain rate reaches 750%/s, and the output power density is as high as 1360 W kg‐1. It is further demonstrated that the LCE‐based motor unit behaves like an actuator, a brake, or a nonlinear spring on demand, analogous to most animal muscles. Finally, as a proof‐of‐concept, multiple highly dexterous artificial neuromuscular systems are demonstrated using the LCE‐based motor unit.
Under electrical stimulation, the actuation strain of the LCE‐based motor unit can reach 45%, the strain rate is as high as 750%/s, and the output power density is as high as 1360 W kg‐1. It is further demonstrated that the LCE‐based motor unit behaves more than an actuator and can be easily integrated into various artificial neuromuscular systems.
Soft electromagnetic artificial muscles (SEAMs) that use electric currents are reported as their power sources. The proposed actuator consists of fully soft components: microfluidic coils, ...stretchable magnets, ferromagnetic silicone, and stretchable housings. The soft coils are fabricated by directly printing room‐temperature liquid metal on a stretchable substrate, enabling the generation of high‐density electromagnetic fields. Based on design optimization through modeling and simulation, the proposed actuators have a characteristic of bistability following the relationships of the forces acting on the components. Depending on the design configurations, the proposed actuators generate contraction and expansion motions as well as vibrations in a bidirectional manner, enabled by electromagnetic actuation. The main advantages of the proposed actuators are fully compliant structures, compact form factors, and short response times, which have not been observed in existing polymer‐based artificial muscles. Another advantage is the self‐detection of the actuation states by measuring the inductance change in the coils. Last, the modular design fully packaged with a coil and magnets in a soft housing makes it possible to easily resize and reconfigure the robotic systems with multiple actuator modules for different applications. Examples of applications demonstrated are a modular crawling robot, energy‐efficient grippers, a multi‐degrees of freedom (DOF) soft manipulator, and a high‐frequency swimming robot.
Soft electromagnetic artificial muscles (SEAMs) are a groundbreaking advancement in soft robotics that use electromagnetic forces to generate lifelike movements. With all soft components, they're highly compliant and versatile for a range of robotic applications, from object manipulation to humanoid robots. SEAMs are poised to revolutionize robotics with their unique combination of flexibility and strength.
Muscles in animals and actuation systems in advanced robots consist not of the actuation component alone; the motive, dissipative, and proprioceptive components exist in a complete set to achieve ...versatile and precise manipulation tasks. We present such a system as a linear electrostatic actuator package incorporated with sensing and braking components. Our modular actuator design is composed of these actuator films and a dielectric fluid, and we examine the performance of the proposed system both theoretically and experimentally. In addition, we introduce a mechanism of optical proprioceptive sensing utilizing the Moiré pattern innately generated on the actuator surface, which allows high-resolution reading of the position of the actuator without noise. The optical sensor is also capable of measuring the force exerted by the actuator. Lastly, we add an electroadhesive brake in the package in parallel with the actuator, introducing a method of mode switching that utilizes all three components and presenting control demonstrations with a robot arm. Our actuation system is compact and flexible and can be easily integrated with various robotic applications.
Soft sensors are becoming more popular in wearables as a means of tracking human body motions due to their high stretchability and easy wearability. However, previous research not only was limited to ...only certain body parts, but also showed problems in both calibration and processing of the sensor signals, which are caused by the high nonlinearity and hysteresis of the soft materials and also by the misplacement and displacement of the sensors during motion. Although this problem can be alleviated through redundancy by employing an increased number of sensors, it will lay another burden of heavy processing and power consumption. Moreover, complete full-body motion tracking has not been achieved yet. Therefore, we propose use of deep learning for full-body motion sensing, which significantly increases efficiency in calibration of the soft sensor and estimation of the body motions. The sensing suit is made of stretchable fabric and contains 20 soft strain sensors distributed on both the upper and the lower extremities. Three athletic motions were tested with a human subject, and the proposed learning-based calibration and mapping method showed a higher accuracy than traditional methods that are mainly based on mathematical estimation, such as linear regression.
A novel soft strain sensor capable of withstanding strains of up to 100% is described. The sensor is made of a hyperelastic silicone elastomer that contains embedded microchannels filled with ...conductive liquids. This is an effort of improving the previously reported soft sensors that uses a single liquid conductor. The proposed sensor employs a hybrid approach involving two liquid conductors: an ionic solution and an eutectic gallium-indium alloy. This hybrid method reduces the sensitivity to noise that may be caused by variations in electrical resistance of the wire interface and undesired stress applied to signal routing areas. The bridge between these two liquids is made conductive by doping the elastomer locally with nickel nanoparticles. The design, fabrication, and characterization of the sensor are presented.
We propose a robotic platform that autonomously manipulates templates that hold fabric patterns during a pattern-forming process without human intervention. The platform performs key functions for ...preprocessing of pattern-forming such as opening, closing, placing, and aligning templates made of large and flexible plastic sheets, and is designed to seamlessly connect and operate with a commercial pattern-forming machine. The main contribution of the proposed system is the design of the centering mechanism, which adaptively aligns templates with different sizes placed on the stage. In this paper, we first describe the design of the proposed device and analyze its vibration characteristics to optimize the input parameters of the main actuator. We then characterize the component of the centering mechanism and test the alignment function of the device. Finally, We demonstrate the performance of our device by integrating it with a commercial pattern-forming machine for an automated sewing process. The device shows an operation time of nine seconds shorter than the duration needed by a trained human worker for the same task in the field. We believe the proposed system will be the first step towards realizing a smart garment factory in the apparel industry.
Modular Textile Sensors
In article number 2308571, Yong‐Lae Park, Jaehoon Kim, and Junhyung Kim, and co‐workers introduce a multi‐modal modular textile sensor system designed for the simultaneous ...recognition of human touch and measurement of contact force. The complete sensor array, featuring multiple sensor modules, requires only two wires to read all sensor outputs, enabled by band‐stop filter circuits and frequency domain analysis. The proposed sensor system can be easily attached to a robot's surface, enhancing both its functionality and safety.
We describe the design, fabrication, and calibration of a highly compliant artificial skin sensor. The sensor consists of multilayered mircochannels in an elastomer matrix filled with a conductive ...liquid, capable of detecting multiaxis strains and contact pressure. A novel manufacturing method comprised of layered molding and casting processes is demonstrated to fabricate the multilayered soft sensor circuit. Silicone rubber layers with channel patterns, cast with 3-D printed molds, are bonded to create embedded microchannels, and a conductive liquid is injected into the microchannels. The channel dimensions are 200 μm (width) × 300 μm (height). The size of the sensor is 25 mm × 25 mm, and the thickness is approximately 3.5 mm. The prototype is tested with a materials tester and showed linearity in strain sensing and nonlinearity in pressure sensing. The sensor signal is repeatable in both cases. The characteristic modulus of the skin prototype is approximately 63 kPa. The sensor is functional up to strains of approximately 250%.
State estimation is one of the key requirements in robot control, which has been achieved by kinematic and dynamic models combined with motion sensors in traditional robotics. However, it is ...challenging to acquire accurate proprioceptive information in soft robots due to relatively high noise levels and hysteretic responses of soft actuators and sensors. In this article, we propose a method of estimating real-time states of soft robots by filtering noisy output signals and including hysteresis in the models using a Bayesian network. This approach is useful in constructing a state observer for soft robot control when both the kinematic model of the actuator and the model of the sensor are used. In our method, we regard a hysteresis function as a conditional random process model. We then introduce a dynamic Bayesian network composed of the actuator and the sensor models of the target system using distribution hysteresis mapping. Finally, we show that solving a Bayesian filtering problem is equivalent to suboptimal state estimation of the soft system. This article describes two ways for defining modeling and filtering; one is by Gaussian process regression combined with an extended Kalman filter, and the other is based on variational inference with a particle filter. While the first approach relaxes the uncertainty level in modeling to Gaussian, the second approach illustrates a general probability distribution. We experimentally validate the proposed methods through real-time state estimation of a sensor-integrated soft robotic gripper. The result shows significant improvement in state estimation compared to conventional estimation methods.
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