Unlike traditional remote control systems for controlling unmanned aerial vehicles (UAVs) and drones, active research is being carried out in the domain of vision-based hand gesture recognition systems for drone control. However, contrary to static a...
To enable unmanned aerial vehicle (UAV) operators to efficiently and intuitively convey their commands to a swarm of UAVs, we propose the use of natural and human-centric input modalities, such as voices and gestures. This paper addresses the fusion...
Recent progress in hand gesture recognition has introduced several natural and intuitive approaches to drone control. However, effectively maneuvering drones in complex environments remains challenging. Drone movements are governed by four independen...
For human–robot gesture-driven control, this paper proposes a deep learning-based approach that employs both static and dynamic gestures to drive and control robots for object-grasping and delivery tasks. The method utilizes two-dimensional Con...
Gesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over th...
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addre...
This research intends to understand whether users would adopt the interactive interface of hand gesture recognition for XRSPACE MANOVA in the virtual-reality environment. Different from the traditional joystick control and external sensors, XRSPACE M...
Assistive technologies (ATs) often have a high-dimensionality of possible movements (e.g., assistive robot with several degrees of freedom or a computer), but the users have to control them with low-dimensionality sensors and interfaces (e.g., switch...
Unlike traditional control systems that rely on physical input devices, facial gesture-based interaction offers a contactless and intuitive method for operating autonomous systems. Recent advances in computer vision and deep learning have enabled the...
This paper details the development of an e-textile gesture controller using screen-printed electrodes to measure Electromyography (EMG); the electrical signals produced in a muscle during its use. The final e-textile consists of 7 fabric electrodes a...
Autonomous drone navigation presents challenges for users unfamiliar with manual flight controls, increasing the risk of collisions. This research addresses this issue by developing a multifunctional drone control system that integrates hand gesture...
This paper outlines the process of developing a low-cost system for home appliance control via real-time hand gesture classification using Computer Vision and a custom lightweight machine learning model. This system strives to enable those with speec...
Many gesture recognition systems with innovative interfaces have emerged for smart home control. However, these systems tend to be energy-intensive, bulky, and expensive. There is also a lack of real-time demonstrations of gesture recognition and sub...
The body tracking systems on the current market offer a wide range of options for tracking the movements of objects, people, or extremities. The precision of this technology is often limited and determines its field of application. This work aimed to...
Accurate and real-time gesture recognition is required for the autonomous operation of prosthetic hand devices. This study employs a convolutional neural network-enhanced channel attention (CNN-ECA) model to provide a unique approach for surface elec...
Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using ges...
Generating realistic and contextually appropriate gestures is crucial for creating engaging embodied conversational agents. Although speech is the primary input for gesture generation, adding controls like gesture velocity, hand height, and emotion i...
AI-driven assistance can help the user perform complex teleoperated tasks, introduce autonomous patterns, or adapt the workbench to objects of interest. On the other hand, the level of assistance should be responsive to the user’s response and...
An ultimate goal for Ubiquitous Computing is to enable people to interact with the surrounding electrical devices using their habitual body gestures as they communicate with each other. The feasibility of such an idea is demonstrated through a wearab...
An authorized traffic controller (ATC) has the highest priority for direct road traffic. In some irregular situations, the ATC supersedes other traffic control. Human drivers indigenously understand such situations and tend to follow the ATC; however...
Musculoskeletal disorders (MSDs) can significantly impact individuals’ quality of life (QoL), often requiring effective rehabilitation strategies to promote recovery. However, traditional rehabilitation methods can be expensive and may lack eng...
Modern wheelchairs, with advanced and robotic technologies, could not reach the life of millions of disabled people due to their high costs, technical limitations, and safety issues. This paper proposes a gesture-controlled smart wheelchair system wi...
In this study, we present a gesture-controlled robotic arm system for small assembly lines. Robotic arms are extensively used in industrial applications; however, they typically require special treatment and qualified personnel to set up and operate...
This work presents a remote control device designed to drive the arm gestures of an assistant humanoid mobile robot. The remote control is a master device with two passive arms configured to replicate the four degrees of freedom of each arm of the or...
Rehabilitation requires repetitive and coordinated movements for effective treatment, which are contingent on patient compliance and motivation. However, the monotony, intensity, and expense of most therapy routines do not promote engagement. Gesture...
The paper presents the possibility of using the Kinect v2 module to control an industrial robot by means of gestures and voice commands. It describes the elements of creating software for off-line and on-line robot control. The application for the Ki...
Predefined, user-independent gesture sets do not account for individual differences in movement patterns and physical limitations. This study presents a personalized wrist–forearm static gesture recognition system for human–computer inter...
Dynamic hand gesture recognition is one of the most significant tools for human–computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network fo...
This paper introduces GECO, a real-time, computer vision-assisted gesture controller for IoT-based smart home systems. The platform uses a markerless MediaPipe interface that combines gesture-driven navigation and command execution, enabling intuitiv...
In pharmaceutical and biomedical industries, manual handling of dangerous chemicals is a leading cause of hazardous exposure to chemicals, toxic burning, and chemical contamination. To counteract these risks, we proposed a gesture-controlled bionic h...
This paper presents a gesture-controlled robotic arm system designed for agricultural harvesting, utilizing a data glove equipped with bending sensors and OptiTrack systems. The system aims to address the challenges of labor-intensive fruit harvestin...
This paper presents a novel soft crawling robot controlled by gesture recognition, aimed at enhancing the operability and adaptability of soft robots through natural human–computer interactions. The Leap Motion sensor is employed to capture han...
Mobile handheld devices, such as smartphones and tablets, have become some of the most prominent ubiquitous terminals within the information and communication technology landscape. Their transformative power within the digital music domain changed th...
This paper presents a novel interface that leverages a smartwatch for controlling industrial robotic arms. By harnessing the gyroscope and advanced gesture recognition capabilities of the smartwatch, our solution facilitates intuitive, real-time mani...
The Leap Motion Controller is a sensor for precise hand tracking; it is a device used for human interaction with computer systems via gestures. The study presented in this paper evaluates its workspace in real-world conditions. An exact replica of a...
Manual assembly remains essential in modern manufacturing, yet the increasing complexity of customised production imposes significant cognitive burdens and error rates on workers. Existing Spatial Augmented Reality (SAR) systems often operate passive...
The increasing integration of 3D technologies and machine learning is fundamentally reshaping mineral sciences and cultural heritage, establishing the foundation for an emerging “Mineralogy 4.0” framework. However, public engagement with...
In this paper, we present our investigation of the 2D Hand Gesture Recognition (HGR) which may be suitable for the control of the Automated Guided Vehicle (AGV). In real conditions, we deal with, among others, a complex background, changing lighting...
The continuous advancement of electronic technology has led to the gradual integration of automated intelligent devices into various aspects of human life. Motion gesture-based human–computer interaction systems offer abundant information, user...
Touchless, mid-air gesture-based interactions with remote devices have been investigated as alternative or complementary to interactions based on remote controls and smartphones. Related studies focus on user elicitation of a gesture vocabulary for o...
This paper describes the development of a low-cost mini-robot that is controlled by visual gestures. The prototype allows a person with disabilities to perform visual inspections indoors and in domestic spaces. Such a device could be used as the oper...
Background: Upper limb loss significantly impacts quality of life, and whereas myoelectric prostheses restore some function, conventional surface electromyography (sEMG) systems face challenges like poor signal quality, high cognitive burden, and sub...
Objective: Pulmonary segmentectomy serves as a crucial approach for treating early-stage lung cancer. However, this procedure demands precise identification of segmental anatomy, and surgeons often need to repeatedly consult the patient’s 3D im...
In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion c...
Leader-follower autonomy (LFA) systems have so far only focused on vehicles following other vehicles. Though there have been several decades of research into this topic, there has not yet been any work on human-vehicle leader-follower systems in the...
This study proposes a telemanipulation framework with two wearable IMU sensors without human skeletal kinematics. First, the states (intensity and direction) of spatial hand-guiding gestures are separately estimated through the proposed state estimat...
With the development of light microscopy, it is becoming increasingly easy to obtain detailed multicolor fluorescence volumetric data. The need for their appropriate visualization has become an integral part of fluorescence imaging. Virtual reality (...
Traditional drone handheld remote controllers, although well-established and widely used, are not a particularly intuitive control method. At the same time, drone pilots normally watch the drone video feed on a smartphone or another small screen atta...
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research...
This paper presents the development of a robotic workstation that integrates a collaborative robot as an assistant, leveraging advanced computer vision techniques to enhance human–robot interaction. The system employs state-of-the-art computer...
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