A soft, self-sensing tensile valve for perceptive soft robots.

Soft inflatable robots are a promising paradigm for applications that benefit from their inherent safety and adaptability. However, for perception, complex connections of rigid electronics both in hardware and software remain the mainstay. Although recent efforts have created soft analogs of individual rigid components, the integration of sensing and control systems is challenging to achieve without compromising the complete softness, form factor, or capabilities.

Pattern design of a liquid metal-based wearable heater for constant heat generation under biaxial strain.

As the wearable heater is increasingly popular due to its versatile applications, there is a growing need to improve the tensile stability of the wearable heater. However, maintaining the stability and precise control of heating in resistive heaters for wearable electronics remains challenging due to multiaxial dynamic deformation with human motion. Here, we propose a pattern study for a circuit control system without complex structure or deep learning of the liquid metal (LM)-based wearable heater.

Review of machine learning methods in soft robotics.

Soft robots have been extensively researched due to their flexible, deformable, and adaptive characteristics. However, compared to rigid robots, soft robots have issues in modeling, calibration, and control in that the innate characteristics of the soft materials can cause complex behaviors due to non-linearity and hysteresis. To overcome these limitations, recent studies have applied various approaches based on machine learning.

Evaluation of Finger Force Control Ability in terms of Multi-finger Synergy.

In this study, finger force control abilities are quantified by the concept of multi-finger synergy in conjunction with uncontrolled manifold (UCM) analysis. Two indices, named repeatability and flexibility, representing features of multi-finger synergy were proposed to overcome the limitation of previously introduced indices, such as floor effects and distortion problems. The proposed indices were applied to stroke patients and healthy adults through specifically designed experiments.

Comprehensive analysis of efficient swimming using articulated legs fringed with flexible appendages inspired by a water beetle.

Drag-based swimming is usually accompanied with the shape change of rowing appendages to generate asymmetric force during the power stroke and recovery stroke. To implement this in an aquatic robot, one may actively control the surface area of its legs during the swimming. However, a small sized robot with a limited number of actuators should adjust the surface area of legs in passive manner.

Quantitative evaluation of hand functions using a wearable hand exoskeleton system.

To investigate, improve, and observe the effect of rehabilitation therapy, many studies have been conducted on evaluating the motor function quantitatively by developing various types of robotic systems. Even though the robotic systems have been developed, functional evaluation of the hand has been rarely investigated, because it is difficult to install a number of actuators or sensors to the hand due to limited space around the fingers. Therefore, in this study, a hand exoskeleton was developed to satisfy the required specifications for evaluating the hand functions including spasticity of finger flexors, finger independence, and multi-digit synergy and algorithms to evaluate such functions were proposed.

Design of hair-like appendages and comparative analysis on their coordination toward steady and efficient swimming.

The locomotion of water beetles has been widely studied in biology owing to their remarkable swimming skills. Inspired by the oar-like legs of water beetles, designing a robot that swims under the principle of drag-powered propulsion can lead to highly agile mobility. But its motion can easily be discontinuous and jerky due to backward motions (i.