Related papers: SmartHand: Towards Embedded Smart Hands for Prosth…
This paper introduces a novel AI vision-enabled pediatric prosthetic hand designed to assist children aged 10-12 with upper limb disabilities. The prosthesis features an anthropomorphic appearance, multi-articulating functionality, and a…
We present a novel underactued humanoid five finger soft hand, the KIT \softhand, which is equipped with cameras in the fingertips and integrates a high performance embedded system for visual processing and control. We describe the…
Tactile sensors have been developed since the early '70s and have greatly improved, but there are still no widely adopted solutions. Various technologies, such as capacitive, piezoelectric, piezoresistive, optical, and magnetic, are used in…
Many amputees throughout the world are left with limited options to personally own a prosthetic arm due to the expensive cost, mechanical system complexity, and lack of availability. The three main control methods of prosthetic hands are:…
Extremely increased unstructured data brought by the large-scale intelligent sensing devices application have big challenges not only in data storing and processing but also power consumption surging. Therefore, to improve energy efficiency…
Bringing tactile sensation to robotic hands will allow for more effective grasping, along with the wide range of benefits of human-like touch. Here we present a 3D-printed, three-fingered tactile robot hand comprising an OpenHand Model O…
Tactile sensing is a essential for skilled manipulation and object perception, but existing devices are unable to capture mechanical signals in the full gamut of regimes that are important for human touch sensing, and are unable to emulate…
Research on tactile sensing has been progressing at constant pace. In robotics, tactile sensing is typically studied in the context of object grasping and manipulation. In this domain, the development of robust, multi-modal, tactile sensors…
Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such…
Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through "intelligent" control, by combining…
Tactile sensing is crucial for robotic hands to achieve human-level dexterous manipulation, especially in scenarios with visual occlusion. However, its application is often hindered by the difficulty of collecting large-scale real-world…
Unlike traditional robotic hands, underactuated compliant hands are challenging to model due to inherent uncertainties. Consequently, pose estimation of a grasped object is usually performed based on visual perception. However, visual…
Robotic dexterous in-hand manipulation, where multiple fingers dynamically make and break contact, represents a step toward human-like dexterity in real-world robotic applications. Unlike learning-based approaches that rely on large-scale…
Objective: The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines. Methods: Here we present a neuroprosthetic system to demonstrate that…
Tactile sensing is critical for robotic grasping and manipulation of objects under visual occlusion. However, in contrast to simulations of robot arms and cameras, current simulations of tactile sensors have limited accuracy, speed, and…
Tactile sensing is of great importance during human hand usage such as object exploration, grasping and manipulation. Different types of tactile sensors have been designed during the past decades, which are mainly focused on either the…
Despite recent advancements, existing prosthetic limbs are unable to replicate the dexterity and intuitive control of the human hand. Current control systems for prosthetic hands are often limited to grasping, and commercial prosthetic…
High-density afferents in the human hand have long been regarded as essential for human grasping and manipulation abilities. In contrast, robotic tactile sensors are typically used to provide low-density contact data, such as…
In this paper, we present our work on developing robot arm prosthetic via deep learning. Our work proposes to use transfer learning techniques applied to the Google Inception model to retrain the final layer for surface electromyography…
Advancements in neural engineering have enabled the development of Robotic Prosthetic Hands (RPHs) aimed at restoring hand functionality. Current commercial RPHs offer limited control through basic on/off commands. Recent progresses in…