Related papers: Field-programmable dynamics in a soft magnetic act…

Soft robotics is an attractive and rapidly emerging field, in which actuation is coupled with the elastic response of the robot's structure to achieve complex deformation patterns. A crucial challenge is the need for multiple control…

Miniature robots are untethered actuators, which have significant potential to make existing minimally invasive surgery considerably safer and painless, and enable unprecedented treatments because they are much smaller and dexterous than…

Soft actuators allow to transform external stimuli to mechanical deformations. Because of their deformational response to external magnetic fields, magnetic gels and elastomers represent ideal candidates for such tasks. Mostly, linear…

In-materia reservoir computing (RC) leverages the intrinsic physical responses of functional materials to perform complex computational tasks. Magnetic metamaterials are exciting candidates for RC due to their huge state space, nonlinear…

Magnetic programming soft machines has great development prospects in the fields of minimally invasive medicine, wearable device and soft robot. However, unrepeatable magnetization and low modulus limits their applications. So far, there…

Soft-growing robots are innovative devices that feature plant-inspired growth to navigate environments. Thanks to their embodied intelligence of adapting to their surroundings and the latest innovation in actuation and manufacturing, it is…

Soft robotic manipulators offer operational advantage due to their compliant and deformable structures. However, their inherently nonlinear dynamics presents substantial challenges. Traditional analytical methods often depend on simplifying…

Magnetic navigation systems, including magnetic tracking systems and magnetic actuation systems, have shown great potential for occlusion-free localization and remote control of intracorporeal medical devices and robots in minimally…

The design of robots that are light, soft, powerful is a grand challenge. Since they can easily adapt to dynamic environments, soft robotic systems have the potential of changing the status-quo of bulky robotics. A crucial component of soft…

High-performance closed-loop control of truly soft continuum manipulators has remained elusive. Experimental demonstrations have largely relied on sufficiently stiff, piecewise architectures in which each actuated segment behaves as a…

We present a computational design system that assists users to model, optimize, and fabricate quad-robots with soft skins.Our system addresses the challenging task of predicting their physical behavior by fully integrating the multibody…

Physical reservoir computing is a computational framework that offers an energy- and computation-efficient alternative to conventional training of neural networks. In reservoir computing, input signals are mapped into the high-dimensional…

Predicting chaotic systems is crucial for understanding complex behaviors, yet challenging due to their sensitivity to initial conditions and inherent unpredictability. Probabilistic Reservoir Computing (RC) is well-suited for long-term…

In this work we present a framework that is capable of accurately representing soft robotic actuators in a multiphysics environment in real-time. We propose a constraint-based dynamics model of a 1-dimensional pneumatic soft actuator that…

The compliant structure of soft robotic systems enables a variety of novel capabilities in comparison to traditional rigid-bodied robots. A subclass of soft fluid-driven actuators known as fiber reinforced elastomeric enclosures (FREEs) is…

Soft robots offer more flexibility, compliance, and adaptability than traditional rigid robots. They are also typically lighter and cheaper to manufacture. However, their use in real-world applications is limited due to modeling challenges…

Advanced machine learning algorithms require platforms that are extremely robust and equipped with rich sensory feedback to handle extensive trial-and-error learning without relying on strong inductive biases. Traditional robotic designs,…

We study the computational complexity theory of smooth, finite-dimensional dynamical systems. Building off of previous work, we give definitions for what it means for a smooth dynamical system to simulate a Turing machine. We then show that…

This study demonstrates that the soft biological tissues of humans can be used as a type of soft body in physical reservoir computing. Soft biological tissues possess characteristics such as stress-strain nonlinearity and viscoelasticity…

Soft robots are interesting examples of hyper-redundancy in robotics, however, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials makes modeling of these robots more complicated. This…