Haodong Chen

University of Maryland, College Park | UMD, UMCP, University of Maryland College Park · A. James Clark School of Engineering

Modern manufacturing faces significant challenges, including efficiency bottlenecks and high error rates in manual assembly operations. To address these challenges, we implement artificial intelligence (AI) and propose a gaze-driven assembly assistant system that leverages artificial intelligence for human-centered smart manufacturing. Our system p...

The quantification of repetitive movements, known as repetitive action counting, is critical in various applications, such as fitness tracking, rehabilitation, and manufacturing operation monitoring. Traditional methods predominantly relied on the estimation of red-green-and-blue (RGB) frames and body pose landmarks to identify the number of action...

This paper presents a novel approach to unmanned aerial vehicle (UAV) control through electrooculography (EOG) based eye movement tracking. The research focuses on developing an interface that translates eye movements into UAV navigation commands, showcasing a unique integration of biometric technology in UAV (i.e., drone) control. To measure horiz...

Repetitive counting (RepCount) is critical in various applications, such as fitness tracking and rehabilitation. Previous methods have relied on the estimation of red-green-and-blue (RGB) frames and body pose landmarks to identify the number of action repetitions, but these methods suffer from a number of issues, including the inability to stably h...

Assembly activity recognition and prediction help to improve productivity, quality control, and safety measures in smart factories. This study aims to sense, recognize, and predict a worker's continuous fine-grained assembly activities in a manufacturing platform. We propose a two-stage network for workers' fine-grained activity classification by l...

Assembly activity recognition and prediction help to improve productivity, quality control, and safety measures in smart factories. This study aims to sense, recognize, and predict a worker's continuous fine-grained assembly activities in a manufacturing platform. We propose a two-stage network for workers' fine-grained activity classification by l...

In this poster, we explain the real-time human-robot collaboration using gestures and speech, including I)•Design a real-time, multi-modal communication HYC system based on gesture and speech recognition. II)• Design and recognize dynamic gestures for communication between a human to an industrial robot. II)• Understand human speech and integrate t...

As artificial intelligence and industrial automation are developing, human-robot collaboration (HRC) with advanced interaction capabilities has become an increasingly significant area of research. In this paper, we design and develop a real-time, multi-model HRC system using speech and gestures. A set of sixteen dynamic gestures is designed for com...

Human Activity Recognition (HAR) using wearable devices such as smart watches embedded with Inertial Measurement Unit (IMU) sensors has various applications relevant to our daily life, such as workout tracking and health monitoring. In this paper, we propose a novel attention-based approach to human activity recognition using multiple IMU sensors w...

Mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patients usually has its individual pattern, thus we adopt clustering-based machine learning technique to find a limited number of motion patterns for upper-limb rehabilitation, so that t...

Computer-assisted cognitive training is an effective intervention for patients with mild cognitive impairment (MCI), which can avoid the disadvantages of traditional cognitive training that consumes a lot of medical resources and is difficult to be standardized. However, many computer-assisted cognitive training systems have unfriendly human-comput...

With the development of industrial automation and artificial intelligence, robotic systems are developing into an essential part of factory production, and the human-robot collaboration (HRC) becomes a new trend in the industrial field. In our previous work, ten dynamic gestures have been designed for communication between a human worker and a robo...

Mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patients usually has its individual pattern, thus we adopt clustering-based machine learning technique to find a limited number of motion patterns for upper-limb rehabilitation, so that t...

Human-robot collaboration (HRC) is a challenging task in modern industry and gesture communication in HRC has attracted much interest. This paper proposes and demonstrates a dynamic gesture recognition system based on Motion History Image (MHI) and Convolutional Neural Networks (CNN). Firstly, ten dynamic gestures are designed for a human worker to...

This paper develops a robotic cognitive rehabilitation therapy (CRT) system to assist patients with mild cognitive impairment (MCI) in block design test (BDT) rehabilitation training. This system bridges the treatment gap that occurs when one physician has several patients to attend to. One physician can set up the BDT training task and simultaneou...

In a human-centered intelligent manufacturing system, every element is to assist the operator in achieving the optimal operational performance. The primary task of developing such a human-centered system is to accurately understand human behavior. In this paper, we propose a fog computing framework for assembly operation recognition, which brings c...

Nowadays, mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patient usually has its individual pattern. Thus it is obviously not an optimal solution to use a single motion generator to suit all patients. Yet it would also be unpractical...

In this paper, two integrated target identification and acquisition algorithms and a GUI simulation tool for automated assembly of parallel manipulators are proposed. They seek to identify the target machine part from the work space, obtain its location and pose parameters, and accomplish its assembling task while avoiding the collision with other...