Related papers: A Soft e-Textile Sensor for Enhanced Deep Learning…
Dynamic control of a soft-body robot to deliver complex behaviors with low-dimensional actuation inputs is challenging. In this paper, we present a computational approach to automatically generate versatile, underactuated control policies…
Growing robots based on the eversion principle are known for their ability to extend rapidly, from within, along their longitudinal axis, and, in doing so, reach deep into hitherto inaccessible, remote spaces. Despite many advantages,…
To foster an immersive and natural human-robot interaction, the implementation of tactile perception and feedback becomes imperative, effectively bridging the conventional sensory gap. In this paper, we propose a dual-modal electronic skin…
With soft robotics being increasingly employed in settings demanding high and controlled contact forces, recent research has demonstrated the use of soft robots to estimate or intrinsically sense forces without requiring external sensing…
Robots play a critical role as the physical agent of human operators in exploring the ocean. However, it remains challenging to grasp objects reliably while fully submerging under a highly pressurized aquatic environment with little visible…
Human limb motion tracking and recognition plays an important role in medical rehabilitation training, lower limb assistance, prosthetics design for amputees, feedback control for assistive robots, etc. Lightweight wearable sensors,…
Stretchable sensors indicate promising prospects for soft robotics, medical devices, and human-machine interactions due to the high compliance of soft materials. Discrete sensing strategies, including sensor arrays and distributed sensors,…
The precise control of soft and continuum robots requires knowledge of their shape, which has, in contrast to classical rigid robots, infinite degrees of freedom. To partially reconstruct the shape, proprioceptive techniques use built-in…
Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based approaches require line-of-sight and complex instrumentation, limiting operation in occluded…
Soft wearable robots are a promising new design paradigm for rehabilitation and active assistance applications. Their compliant nature makes them ideal for complex joints like the shoulder, but intuitive control of these robots require…
Soft robots could bring robotic systems to new horizons, by enabling safe human-machine interaction. For precise control, these soft structures require high level position feedback that is not easily achieved through conventional…
Force and proximity sensors are key in robotics, especially when applied in collaborative robots that interact physically or cognitively with humans in real unstructured environments. However, most existing sensors for use in robotics are…
Accurately simulating soft tissue deformation is crucial for surgical training, pre-operative planning, and real-time haptic feedback systems. While physics-based models such as the finite element method (FEM) provide high-fidelity results,…
Physical interaction with textiles, such as assistive dressing, relies on advanced dextreous capabilities. The underlying complexity in textile behavior when being pulled and stretched, is due to both the yarn material properties and the…
To adapt to constantly changing environments and be safe for human interaction, robots should have compliant and soft characteristics as well as the ability to sense the world around them. Even so, the incorporation of tactile sensing into…
Tactile servoing is an important technique because it enables robots to manipulate objects with precision and accuracy while adapting to changes in their environments in real-time. One approach for tactile servo control with high-resolution…
Soft robotics have gained increased attention from the robotic community due to their unique features such as compliance and human safety. Impressive amount of soft robotic prototypes have shown their superior performance over their rigid…
In this paper, a novel fully 3D, microfluidic-oriented, gel-based, and low-cost highly stretchable resistive sensors have been presented. By the proposed method we are able to measure and discriminate all of the stretch, twist, and pressure…
Recently, deep learning becomes the main focus of machine learning research and has greatly impacted many important fields. However, deep learning is criticized for lack of interpretability. As a successful unsupervised model in deep…
This paper presents a learning-based approach for accurately estimating the 3D shape of flexible continuum robots subjected to external loads. The proposed method introduces a spatiotemporal neural network architecture that fuses…