arXiv subjects

Thuong Hoang

Publications and source records attributed to Thuong Hoang.

13 recordsLinked to original sources

arXiv2026

A Four-Tier Communication Architecture and Sim-to-Real Validation of a Graphical Open-Source Platform for Robotic Engineering Education

The persistent challenge in scaling authentic manipulator education within university laboratories is a structural dichotomy: commercial digital twins are often cost-prohibitive and rigidly scripted, whereas open-source robotics middleware (ROS) imposes steep technical and syntax barriers for novices. To resolve this logistical and educational friction, this paper proposes a scalable four-tier communication architecture tailored for sustainable robotic curricula. Rather than focusing on software application design, our study examines the underlying data exchange mechanisms required to bridge visual conceptual environments with physical robotic endpoints, utilizing the Graphical Open-Source Platform (GOSP) as a reference implementation. Our work details the framework's technical integration of 3D visual armature modeling with a robust ROS middleware backend, emphasizing the serialization, routing, and encapsulation of intricate communication routines. Preliminary sim-to-real validation using multi-axis spatial trajectories confirms that encapsulating these communication pipelines provides sufficient fidelity and a hardware-agnostic pathway. By bridging virtual design and physical execution, our architectural blueprint offers a viable infrastructure for engineering education.

cs.HC↗

arXiv2026

Edge-Based QoS-Aware Adaptive Task Placement: A Closed-Loop Control in Multi-Robot Systems

Multi-robot systems (MRS) increasingly offload compute-intensive perception tasks to edge nodes to meet strict time-sensitive Quality-of-Service (QoS) constraints. However, static task orchestration on a shared edge node can severely degrade QoS due to network latency, jitter, and edge-resource contention. We present a pilot edge-centric MRS testbed using Raspberry Pi nodes to evaluate a camera-to-manipulator pipeline under three modes: local execution, static offloading, and a QoS-aware Adaptive Task Placement (ATP) controller. ATP scores candidate placements using a multi-metric cost (normalized latency, CPU utilization, and switching overhead) over two-second control windows. The closed-loop visual servoing testbed is instrumented with sub-millisecond clock synchronization, network emulation, and detailed monitoring of multiple metrics across nodes to capture realistic jitter. Experimental results under compute-stress and network-fault scenarios show that static edge offloading reduces on-board CPU load but amplifies tail latency and deadline misses. In contrast, the QoS-aware ATP controller, by switching task placement based on measured latency and utilization thresholds, consistently lowers deadline violations and tail latency. Overall, the results position ATP as a practical edge-side control primitive for MRS and concrete design guidelines for Cloud-Edge Robotics deployments within the broader cloud-fog automation, while motivating QoS-aware multi-objective workload orchestration for industrial cyber-physical systems.

cs.OS↗

arXiv2026

DAG-Based QoS-Aware Dynamic Task Placement for Networked Multi-Stage Control Pipelines

Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally intensive onboard due to complex models embedded on robots. In practice, offloading the perception task to on-site edges statically is inappropriate for latency-sensitive, precise industrial settings over a standardized industrial network. This emphasizes the importance of Control-Communication-Computing (3C) co-design in industrial automation: monolithic local execution saturates AI-accelerated machine and robot hardware, while static edge offloading exposes the control loop to network jitter. Existing adaptive task placement (ATP) controllers can partially address the gap by relocating a single pipeline stage on binary threshold rules, without a multi-stage model and an explicit cost on placement switching. In this paper, we propose a directed acyclic graph (DAG) based quality-of-service (QoS)-aware dynamic task placement (DTP) framework for sensing-perception-planning-control pipelines in networked robotics. This pipeline is formalized as a DAG with task-level and node-level attributes for compute cost, communication delay, and feasible placement sets; over a small interpretable candidate set (fully local, static offload, hybrid), a window-based cost function combines tail end-to-end latency, deadline violation rate, hardware utilization, and a Hamming-distance switching penalty, and a DTP algorithm with hysteresis and a minimum dwell-time bounds placement chatter. Our work presents the theoretical framework, a structured qualitative analysis, and a two-phase simulation plus hardware-in-the-loop validation roadmap.

cs.DC↗

arXiv2026

BICEP/Keck XXI: Constraints on Early-Universe Parity Violation from Multipole-Dependent Birefringence

We present the first constraints on multipole-dependent cosmic birefringence using CMB polarization data from the BK18 dataset, which combines observations from BICEP2, Keck Array, and BICEP3 at frequencies of 95, 150, and 220 GHz. Photon coupling to an axion-like field leads to the rotation of CMB polarization, inducing non-zero EB cross-correlations. We show that a multipole-dependent rotation beta(l) imprints a distinct signature in the polarization spectra that can be constrained. Specifically, we consider an Early Dark Energy (EDE) scenario in which a pseudoscalar field couples to photons through a Chern-Simons interaction, generating a polarization rotation with multipole dependence. We introduce a phenomenological beta(l) as a step function, obtaining constraints on the step function size consistent with zero, with uncertainties less than 0.15 degrees (68% CL). In addition, using multi-frequency EE, BB, and EB cross-spectra, along with robust BICEP/Keck foreground treatment and likelihood framework, we derive constraints on the axion-photon coupling amplitude g for several choices of EDE parameters. For the baseline best-fit value f_{EDE} = 0.087 from the Planck 2018 analysis, we obtain g = 0.11 +/- 0.37 (68% CL), consistent with previous limits.

astro-ph.CO↗

arXiv2026

Auto-Generating Personas from User Reviews in VR App Stores

Personas are a valuable tool for discussing accessibility requirements in software design and development practices. However, the use of personas for accessibility-focused requirements elicitation in VR projects remains limited and is accompanied by several challenges. To fill this gap, we developed an auto-generated persona system in a VR course, where the personas were used to facilitate discussions on accessibility requirements and to guide VR design and development. Our findings indicate that the auto-generated persona system enabled students to develop empathy more efficiently. This study demonstrates the use of automatically generated personas in VR course settings as a means of eliciting latent accessibility requirements.

cs.HC↗

arXiv2026

VRARE: Using Virtual Reality to Understand Accessibility Requirements of Color Blindness and Weakness

In this paper, we developed a virtual reality (VR) system that can simulate color blindness and weakness. We built an immersive 3D web view interface where participants can discuss accessibility requirements for a fitness website projects within a virtual fitness environment. We conducted a pilot experiment involving 24 participants from six software teams, who used both VR and non-VR methods to understand color blindness and weakness requirements in a website project. Our findings indicate that using VR can provide several benefits for requirements activities, such as an improved user experience and reduced workload.

cs.HC↗

arXiv2026

Discussing Your Needs in VR: A Novel Approach through Persona-based Stakeholder Role-Playing

In this study, we propose a novel approach that supports requirements discussions in virtual environments by automatically generating personas from real-time speech-to-text data. In our pilot experiment, 18 participants (14 from universities and 4 from IT companies) used the generated personas to discuss accessibility requirements within the virtual environment. Participants reported a relatively high level of satisfaction with the social presence and usability of the VR system. We also found that requirements discussions based on personas have a lower workload. Finally, we outline the main directions for future work.

cs.HC↗

arXiv2025

Investigating VR Accessibility Reviews for Users with Disabilities: A Qualitative Analysis

Accessibility reviews provide valuable insights into both the limitations and benefits experienced by users with disabilities when using virtual reality (VR) applications. However, a comprehensive investigation into VR accessibility for users with disabilities is still lacking. To fill this gap, this study analyzes user reviews from the Meta and Steam stores of VR apps, focusing on the reported issues affecting users with disabilities. We applied selection criteria to 1,367,419 reviews from the top 40, the 20 most popular, and the 40 lowest-rated VR applications on both platforms. In total, 1,076 (0.078%) VR accessibility reviews referenced various disabilities across 100 VR applications. These applications were categorized into Action, Sports, Social, Puzzle, Horror, and Simulation, with Action receiving the highest number of accessibility related-reviews. We identified 16 different types of disabilities across six categories. Furthermore, we examined the causes of accessibility issues as reported by users with disabilities. Overall, VR accessibility reviews were predominantly under-supported.

cs.SE↗

arXiv2025

How Long Does It Take to Alleviate Discomfort? A Preliminary Study on Reducing Cybersickness in Novice Users

Cybersickness significantly impacts the user experience in VR applications. Locomotion tunneling is a widely adopted technique for mitigating cybersickness in susceptible users. However, there is a lack of research investigating the effects of prolonged use of locomotion tunneling among novice users. To fill this gap, we used VRChat as our experimental platform. We recruited 24 novice VR users, defined as participants with no prior experience using immersive virtual environments. We collected five days of data within a one-week period. The results indicated that participants exhibited significant mitigation to cybersickness by Day 4. However, a change in the VR scene on Day 5 led to a notable increase in cybersickness symptoms. Qualitative feedback revealed participant-perceived causes of cybersickness and suggested that the effectiveness of locomotion tunneling was limited in some scenarios. Finally, we discussed the limitations of the study and proposed directions for future research.

cs.HC↗

arXiv2025

CFTel: A Practical Architecture for Robust and Scalable Telerobotics with Cloud-Fog Automation

Telerobotics is a key foundation in autonomous Industrial Cyber-Physical Systems (ICPS), enabling remote operations across various domains. However, conventional cloud-based telerobotics suffers from latency, reliability, scalability, and resilience issues, hindering real-time performance in critical applications. Cloud-Fog Telerobotics (CFTel) builds on the Cloud-Fog Automation (CFA) paradigm to address these limitations by leveraging a distributed Cloud-Edge-Robotics computing architecture, enabling deterministic connectivity, deterministic connected intelligence, and deterministic networked computing. This paper synthesizes recent advancements in CFTel, aiming to highlight its role in facilitating scalable, low-latency, autonomous, and AI-driven telerobotics. We analyze architectural frameworks and technologies that enable them, including 5G Ultra-Reliable Low-Latency Communication, Edge Intelligence, Embodied AI, and Digital Twins. The study demonstrates that CFTel has the potential to enhance real-time control, scalability, and autonomy while supporting service-oriented solutions. We also discuss practical challenges, including latency constraints, cybersecurity risks, interoperability issues, and standardization efforts. This work serves as a foundational reference for researchers, stakeholders, and industry practitioners in future telerobotics research.

cs.DC↗

arXiv2025

Leveraging Cloud-Fog Automation for Autonomous Collision Detection and Classification in Intelligent Unmanned Surface Vehicles

Industrial Cyber-Physical Systems (ICPS) technologies are foundational in driving maritime autonomy, particularly for Unmanned Surface Vehicles (USVs). However, onboard computational constraints and communication latency significantly restrict real-time data processing, analysis, and predictive modeling, hence limiting the scalability and responsiveness of maritime ICPS. To overcome these challenges, we propose a distributed Cloud-Edge-IoT architecture tailored for maritime ICPS by leveraging design principles from the recently proposed Cloud-Fog Automation paradigm. Our proposed architecture comprises three hierarchical layers: a Cloud Layer for centralized and decentralized data aggregation, advanced analytics, and future model refinement; an Edge Layer that executes localized AI-driven processing and decision-making; and an IoT Layer responsible for low-latency sensor data acquisition. Our experimental results demonstrated improvements in computational efficiency, responsiveness, and scalability. When compared with our conventional approaches, we achieved a classification accuracy of 86\%, with an improved latency performance. By adopting Cloud-Fog Automation, we address the low-latency processing constraints and scalability challenges in maritime ICPS applications. Our work offers a practical, modular, and scalable framework to advance robust autonomy and AI-driven decision-making and autonomy for intelligent USVs in future maritime ICPS.

cs.DC↗

arXiv2024

Who Uses Personas in Requirements Engineering: The Practitioners' Perspective

Personas are commonly used in software projects to gain a better understanding of end-users' needs. However, there is a limited understanding of their usage and effectiveness in practice. This paper presents the results of a two-step investigation, comprising interviews with 26 software developers, UI/UX designers, business analysts and product managers and a survey of 203 practitioners, aimed at shedding light on the current practices, methods and challenges of using personas in software development. Our findings reveal variations in the frequency and effectiveness of personas across different software projects and IT companies, the challenges practitioners face when using personas and the reasons for not using them at all. Furthermore, we investigate the coverage of human aspects in personas, often assumed to be a key feature of persona descriptions. Contrary to the general perception, our study shows that human aspects are often ignored for various reasons in personas or requirements engineering in general. Our study provides actionable insights for practitioners to overcome challenges in using personas during requirements engineering stages, and we identify areas for future research.

cs.SE↗

arXiv2023

Multi-Modal Emotion Recognition for Enhanced Requirements Engineering: A Novel Approach

Requirements engineering (RE) plays a crucial role in developing software systems by bridging the gap between stakeholders' needs and system specifications. However, effective communication and elicitation of stakeholder requirements can be challenging, as traditional RE methods often overlook emotional cues. This paper introduces a multi-modal emotion recognition platform (MEmoRE) to enhance the requirements engineering process by capturing and analyzing the emotional cues of stakeholders in real-time. MEmoRE leverages state-of-the-art emotion recognition techniques, integrating facial expression, vocal intonation, and textual sentiment analysis to comprehensively understand stakeholder emotions. This multi-modal approach ensures the accurate and timely detection of emotional cues, enabling requirements engineers to tailor their elicitation strategies and improve overall communication with stakeholders. We further intend to employ our platform for later RE stages, such as requirements reviews and usability testing. By integrating multi-modal emotion recognition into requirements engineering, we aim to pave the way for more empathetic, effective, and successful software development processes. We performed a preliminary evaluation of our platform. This paper reports on the platform design, preliminary evaluation, and future development plan as an ongoing project.

cs.SE↗