Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compact form factors can detect only a single deformation mode at a time due to the limitation in combining multiple sensing mechanisms in a limited space. However, realizing multiple modalities in a soft sensor without increasing its original form factor is beneficial, because even a single input stimulus to a robot may induce a combination of multiple modes of deformation. Here, we report a multifunctional soft sensor capable of decoupling combined deformation modes of stretching, bending, and compression, as well as detecting individual deformation modes, in a compact form factor. The key enabling design feature of the proposed sensor is a combination of heterogeneous sensing mechanisms: optical, microfluidic, and piezoresistive sensing. We characterize the performance on both detection and decoupling of deformation modes, by implementing both a simple algorithm of threshold evaluation and a machine learning technique based on an artificial neural network. The proposed soft sensor is able to estimate eight different deformation modes with accuracies higher than 95%. We lastly demonstrate the potential of the proposed sensor as a method of human-robot interfaces with several application examples highlighting its multifunctionality.
We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.
The electroadhesion pad is mainly studied for applications, such as climbing robots and grippers. In this paper, we present our study with the confirmation of the adhesion properties of the electroadhesion pad with a double-insulating layer, pad modeling, and optimal design. Modeling and analysis consider the air layer generated during the manufacturing of both conventional single-insulated structures and dual-insulated structures. Through the finite element analysis simulation, the characteristics of the electroadhesion were verified, and modeling verification was performed, based on the variables that had a large influence as follows: applied voltage, electrode area, dielectric thickness, and permittivity. The electrode is made of aluminum, the substrate is made of silicon, and the dielectric is made of polyimide film. An error of up to 8.3% was found between the modeling and simulation. The optimization results were validated based on a pad applied to a climbing robot measuring 320×480mm² and weighing 2.8 kg. As a result, the optimal pad design resulted in an error of 7.3% between the modeling and simulation.
The milling of highly flexible workpieces, such as thin-walled structures used in turbine blades, aerospace equipment, and jet engine compressors, requires vibration compensation to improve the quality of the workpiece surface. Vibration can be reduced by selecting appropriate cutting parameters. However, this approach reduces system productivity. This paper presents an active workpiece holder that controls the vibration of general computer numerical control machine tools. The proposed holder, which comprises a flexible guide mechanism, driver, and sensor, measures vibration and actively controls it using piezoactuators. A high-rigidity flexure mechanism was designed for the holder, and finite element method simulation and modal analysis were performed. Finally, the proposed system was fabricated, and experimental verification indicated that the system reduced vibration. The surface quality obtained using the controlled system was ∼50% better than that obtained using the uncontrolled system.
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