This work presents a self-sensing artificial muscle (SSAM) that can sense its length change as small as 0.01 mm via a seamlessly integrated multi-segment induction coil. The SSAM provides accurate length information regardless of its loadings, driving pressure, or muscle design, adequate for robust data-driven feedback control. An SSAM-based artificial arm is demonstrated for humanlike spontaneously perception, interaction, and sensing-based positioning.
Inspired by the human fingers, this work presents a biomimetic soft finger (BSF) with seamlessly integrated conductive fiber coil, which is capable of monitoring its bending angle and force at the fingertip with a resolution of 0.02° and 0.4 mN, respectively. The fiber coil's inductance decreases with the bending angle and its resistance increases with the force at the twisted LM fiber. The BSF can detect stiffness by a simple touch, and was demonstrated for lump searching and taking pulses like a “Robodoctor”.
This paper presents a soft inductive bimodal sensor (SIBS) with decoupled force and bending sensing by measuring the inductance at two different frequencies. The SIBS exploits the eddy-current effect at high frequency for 1 mN force sensing and the magnetic reluctance effect at medium frequency for bending sensing (0.44°). We demonstrated the SIBS for perception of a soft crawling robot, and as a wearable human-machine interface on the wrist to interactively control a soft locomotion robot.
Here, we present a self-displacement sensing solution for SEMAs without requiring additional hardware. A self-displacement sensing and driving circuit (SDSDC) was developed and evaluated, in which low-frequency driving and high-frequency sensing signals can function simultaneously without interfering with each other, with a sensing resolution of 0.03 µm. It shows promising features for applications from auto-focus lens, voice coil motors, haptic feedback devices and metaverse.
This paper presents a fully integrated, reconfigurable MFS (RMFS), which utilizes an array of PCB coils to detect the multiaxis displacement/rotation of a metal target at high resolution without mechanical or electrical connections. The RMFS prototype achieved an ultrahigh resolution of 1 mN for triaxial force sensing in a range of 20 N. The RMFS shows promising features to be implemented in diverse applications from robotics, human-machine-interaction, and biomedical systems.
In this work, we propose a non-array soft tactile sensor (NA-STS) that utilizes two triangle textile electrodes and a rectangle electrode to form a pair of soft capacitive pressure sensors in a differential configuration along its length. The results show that the NA-STS can detect the force as low as 2.1mN and a maximum error of 2.5 mm for contact location. The NA-STS has a simple structure, high performance and rapid response, immune to proximity effect, and robust for real-word applications.
Here we presented a printed induction-based array sensor with only two signal terminals. It identifies the material species of approaching and touching objects and also recognizes the speed and shapes of the objects moving dynamically above the sensor. It is demonstrated that a finger-like array sensor with two terminals could provide a simple and reliable structural design for the new robotic applications of material recognition and stimuli position detection.
In this work, we propose a film-like split angle sensor (FSAS) which operates through AC magnetic field coupling between a soft planar coil and a ferromagnetic or conductive target film. The FSAS has a split configuration, overcoming the movement impairment problem presented by the strain sensing approach. It was demonstrated for angle sensing and external force detection of a laptop lid, wearable angle monitoring of elbow, and perception of a pneumatic driven origami robot.
A reconfigurable and proprioceptive soft origami module is presented, where two actuation modes (i.e., extension and bending) are realized. Multimodal perception is enabled using a novel foldable self-inductance sensor. An intelligent gripper is capable of grasping mode adjustment, grasping force measurement, and the grasping target’s size measurement. Moreover, an intelligent jellyfish is presented, with buoyancy adjustment and underwater grasping capabilities.