相关论文: Human Robot Interface for Assistive Grasping

To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object…

This project introduces a Feeding Assistive Robot tailored to individuals with physical disabilities, including those with limited arm function or hand control. The core component is a precise 6-degree freedom robotic arm, operated…

While shared autonomy offers significant potential for assistive robotics, key questions remain about how to effectively map 2D control inputs to 6D robot motions. An intuitive framework should allow users to input commands effortlessly,…

AI has revolutionized the processing of various services, including the automatic facial verification of people. Automated approaches have demonstrated their speed and efficiency in verifying a large volume of faces, but they can face…

This paper presents a control interface to translate the residual body motions of individuals living with severe disabilities, into control commands for body-machine interaction. A custom, wireless, wearable multi-sensor network is used to…

Assistive robotic grasping plays an important role in enabling safe and adaptive manipulation of diverse objects. However, existing systems often rely on electronic sensing and multi-stage processing pipelines, increasing system complexity…

Interaction in virtual reality (VR) environments is essential to achieve a pleasant and immersive experience. Most of the currently existing VR applications, lack of robust object grasping and manipulation, which are the cornerstone of…

Individuals with upper limb movement limitations face challenges in interacting with others. Although robotic arms are currently used primarily for functional tasks, there is considerable potential to explore ways to enhance users' body…

Assistive robotic devices can increase the independence of individuals with motor impairments. However, each person is unique in their level of injury, preferences, and skills, which moreover can change over time. Further, the amount of…

This paper introduces a novel and general method to address the problem of using a general-purpose robot manipulator with a parallel gripper to wrap a deformable linear object (DLO), called a rope, around a rigid object, called a rod,…

Human demonstrations are important in a range of robotics applications, and are created with a variety of input methods. However, the design space for these input methods has not been extensively studied. In this paper, focusing on…

Electromyography (EMG) has been explored as an HCI input modality following a long history of success for prosthesis control. While EMG has the potential to address a range of hands-free interaction needs, it has yet to be widely accepted…

Dynamic hand gestures play a pivotal role in assistive human-robot interaction (HRI), facilitating intuitive, non-verbal communication, particularly for individuals with mobility constraints or those operating robots remotely. Current…

Robots assist in many areas that are considered unsafe for humans to operate. For instance, in handling pandemic diseases such as the recent Covid-19 outbreak and other outbreaks like Ebola, robots can assist in reaching areas dangerous for…

This work focuses on closed-loop control based on proprioceptive feedback for a pneumatically-actuated soft wearable device aimed at future support of infant reaching tasks. The device comprises two soft pneumatic actuators (one…

Novel robotic grippers have captured increasing interests recently because of their abilities to adapt to varieties of circumstances and their powerful functionalities. Differing from traditional gripper with mechanical components-made…

In the past two decades, there has been a continuous rise in the deployment of robots fulfilling social roles that expands across various industries such as guides, service providers, and educators. To establish robots as integral allies in…

In this paper, we aim at improving human motion prediction during human-robot collaboration in industrial facilities by exploiting contributions from both physical and physiological signals. Improved human-machine collaboration could prove…

Objective: Multimodal hand gesture recognition (HGR) systems can achieve higher recognition accuracy compared to unimodal HGR systems. However, acquiring multimodal gesture recognition data typically requires users to wear additional…

Accurate human motion prediction (HMP) is critical for seamless human-robot collaboration, particularly in handover tasks that require real-time adaptability. Despite the high accuracy of state-of-the-art models, their computational…