相关论文: Grab-n-Go: On-the-Go Microgesture Recognition with…
Handheld grippers are increasingly used to collect human demonstrations due to their ease of deployment and versatility. However, most existing designs lack tactile sensing, despite the critical role of tactile feedback in precise…
Due to the universal non-verbal natural communication approach that allows for effective communication between humans, gesture recognition technology has been steadily developing over the previous few decades. Many different strategies have…
In this work, we present a reconfigurable data glove design to capture different modes of human hand-object interactions, which are critical in training embodied artificial intelligence (AI) agents for fine manipulation tasks. To achieve…
Direct and natural interaction is essential for intuitive human-robot collaboration, eliminating the need for additional devices such as joysticks, tablets, or wearable sensors. In this paper, we present a lightweight deep learning-based…
Eye movement is closely related to limb actions, so it can be used to infer movement intentions. More importantly, in some cases, eye movement is the only way for paralyzed and impaired patients with severe movement disorders to communicate…
Tactile sensing is used by humans when grasping to prevent us dropping objects. One key facet of tactile sensing is slip detection, which allows a gripper to know when a grasp is failing and take action to prevent an object being dropped.…
Natural user interfaces are on the rise. Manufacturers for Augmented, Virtual, and Mixed Reality head mounted displays are increasingly integrating new sensors into their consumer grade products, allowing gesture recognition without…
Providing users with accurate gestural interfaces, such as gesture recognition based on wrist-worn devices, is a key challenge in mixed reality. However, static machine learning processes in gesture recognition assume that training and test…
This study describes and evaluates i-GRIP, a novel movement intention estimator designed to facilitate the control of assistive devices for grasping tasks in individuals with upper limb impairments. Operating within a collaborative grasping…
Gaze gestures can provide hands free input on mobile devices, but practical use requires (i) gestures users can learn and recall and (ii) recognition models that are efficient enough for on-device deployment. We present an end-to-end…
Detection of slip during object grasping and manipulation plays a vital role in object handling. Existing solutions primarily rely on visual information to devise a strategy for grasping. However, for robotic systems to attain a level of…
In this paper, we propose a micro hand gesture recognition system and methods using ultrasonic active sensing. This system uses micro dynamic hand gestures for recognition to achieve human-computer interaction (HCI). The implemented system,…
Understanding objects through multiple sensory modalities is fundamental to human perception, enabling cross-sensory integration and richer comprehension. For AI and robotic systems to replicate this ability, access to diverse, high-quality…
Hand-face interactions play a key role in many everyday tasks, providing insights into user habits, behaviors, intentions, and expressions. However, existing wearable sensing systems often struggle to track these interactions in daily…
Daily objects embedded in a contextual environment are often ungraspable initially. Whether it is a book sandwiched by other books on a fully packed bookshelf or a piece of paper lying flat on the desk, a series of nonprehensile pregrasp…
Gesture recognition is a very essential technology for many wearable devices. While previous algorithms are mostly based on statistical methods including the hidden Markov model, we develop two dynamic hand gesture recognition techniques…
Grasping constitutes a critical challenge for visually impaired people. To address this problem, we developed a tactile bracelet that assists in grasping by guiding the user's hand to a target object using vibration commands. Here we…
People spend an enormous amount of time and effort looking for lost objects. To help remind people of the location of lost objects, various computational systems that provide information on their locations have been developed. However,…
In our daily life, we often encounter objects that are fragile and can be damaged by excessive grasping force, such as fruits. For these objects, it is paramount to grasp gently -- not using the maximum amount of force possible, but rather…
Wearable biosensor technology enables real-time, convenient, and continuous monitoring of users behavioral signals. Such include signals relative to body motion, body temperature, biological or biochemical markers, and individual grip…