Lab

XRAI Lab

The Extended Reality, Artificial Intelligence, and Robotics (XRAI) Lab aims to advance the seamless integration of Extended Reality (XR), Artificial Intelligence (AI), and Robotics to create intelligent, interactive, and adaptive systems. Our research focuses on next-generation technologies that seamlessly bridge the physical and virtual worlds, enabling intuitive human–machine interaction, augmenting human capabilities, and supporting collaborative autonomy.

Through interdisciplinary innovation, the XRAI Lab redefines how intelligent systems are designed, experienced, and deployed across real-world applications, including advanced manufacturing, engineering education, and human-centered automation.

Research Focus

Human-Centered XR & AI
1

Human-Centered XR & AI

Studying how people perceive and interact within XR environments to design intuitive, cognitively-aware, AI-enhanced interfaces.

Human Factors Spatial Perception Healthcare Cognitive Systems
Immersive Learning & Workforce Training
2

Immersive Learning & Workforce Training

Designing and evaluating XR-based systems that accelerate skill acquisition, knowledge transfer, and workforce readiness across education and professional domains.

Higher Education K–12 Emergency Response Technical Training
XR-Mediated Human-Robot Collaboration
3

XR-Mediated Human-Robot Collaboration

Developing XR interfaces that enable natural, safe, and efficient communication between humans and robotic systems in complex real-world environments.

Industrial Robotics Teleoperation Collaborative Manufacturing Remote Operations
Digital Twin & Intelligent Manufacturing
4

Digital Twin & Intelligent Manufacturing

Integrating digital twin and AR technologies to build data-driven manufacturing environments with intelligent visualization, monitoring, and maintenance workflows.

Predictive Maintenance Smart Factory Industrial IoT Quality Control
Adaptive & Intelligent XR Systems
5

Adaptive & Intelligent XR Systems

Building AI-driven XR pipelines that sense user context, adapt in real time, and deliver personalized interaction across rehabilitation, training, and industrial settings.

Rehabilitation Personalized Training AI-Assisted Interaction Spatial Computing

Team

Principal Investigator

Wenhao Yang

Wenhao Yang

Assistant Professor

Dr. Victor A. Zaloom Department of Industrial and Systems Engineering

College of Engineering

Lamar University, 4400 MLK Blvd., PO Box 10009, Beaumont, Texas 77710

Office: Cherry Engineering Building, Room 2628 · Tel: 409-880-1891

Doctoral Students

Lakshmana Ayyalasomayajula (Avinash)

Lakshmana Ayyalasomayajula (Avinash)

DE Student

Mohammad Asifur R Rabby

Mohammad Asifur R Rabby

DE Student

Rezwanul Ashraf Ruddro

Rezwanul Ashraf Ruddro

DE Student

Paniz Bioucki

Paniz Bioucki

DE Student

Rohith Naini

Rohith Naini

DE Student

Master’s Students

Amrit Silwal

Amrit Silwal

M.S. Student

Undergraduate Researchers

Ayden J Hicks

Ayden J Hicks

Undergraduate Research Assistant

Alumni

NameDegreeDurationThesisCurrent Position
Rezwanul Ashraf Ruddro M.S. Industrial Engineering 2025 – 2026 Development of an Immersive VR Learning System With LLM-Integrated Avatar for Educational Assistance Continuing DE student at Lamar University
Muhammad Ilyas Mubarik M.S. Industrial Engineering 2024 – 2026 Advanced Mixed Reality Training for First Responders in Hurricane Scenarios Operations Tech II @ Amazon Data Center Engineering Operations

Collaborators

Administrative Support

Heather Martindale is helping us (and other groups) with administration.

Join the Lab

We are recruiting students for two degree paths in Industrial Engineering at Lamar University:

  • Doctor of Engineering (D.E.) in Industrial Engineering
  • Master’s degree, thesis option

You will fit in well if you use AI tools in your work, can code, and have experience with any of Unity, ROS 2, Python, or user studies.

There are no funded (RA) positions at this time. Admission to either program goes through Lamar University’s graduate application.

If you would like to work with the XRAI Lab, email wenhao.yang@lamar.edu with:

  1. your CV, and
  2. a short description of a research idea you want to pursue — ideally connected to one of the research focus areas above.

Recent Research

Path Planning Using Industrial Robotics for Automation of Route-Based Vibration Data Collection

Route-based vibration data collection remains a manual task in industrial condition monitoring: technicians walk predefined equipment routes with portable collectors on weekly to quarterly schedules, which is labor-intensive and introduces operator-to-operator variability. This project develops an autonomous mobile robot platform that replicates the route definition and execution logic of commercial vibration analysis software. A TurtleBot 4 running ROS 2 is driven by a custom browser-based control panel (connected over rosbridge) that supports manual teleoperation, live SLAM mapping, waypoint capture, and grouping of waypoints into named, color-coded inspection routes with per-point wait, skip, and arrival-error parameters. Route order is optimized as a Traveling Salesman Problem using exact permutation search for small waypoint sets and a nearest-neighbor with 2-opt heuristic for larger ones, while navigation is executed through the Nav2 stack (Dijkstra-based global planning on an inflated costmap, DWB local control, and behavior-tree recovery). The system logs arrival error at every measurement point, captures a camera snapshot on arrival, and exports per-route results to Excel. Validation in a controlled indoor environment demonstrates repeatable multi-route execution and provides the navigation foundation for mounting a vibration sensing payload.

Equipment

Universal Robots UR10e

Collaborative Robot

Universal Robots UR10e

Description

A 6-DOF collaborative robot arm with a 12.5 kg payload, 1300 mm reach, and a force/torque sensor built into the tool flange. It anchors our robot cell for teaching and research in collaborative automation.

Accessories (7)
  • WINGMAN Cobot Tool Changer · TripleA Robotics
  • Screwdriving Solution · Robotiq
  • EPick Vacuum Gripper · Robotiq
  • 2F-85 Adaptive Gripper · Robotiq
  • Wrist Camera · Robotiq
  • Academy Hardware Set · Universal Robots
  • nanoScan3 Core Safety Laser Scanners · SICK

UFACTORY xArm 6

Collaborative Robot

UFACTORY xArm 6

Description

A lightweight 6-DOF collaborative robot arm with a 5 kg payload, 700 mm reach, and ±0.1 mm repeatability, fully open to programming from Python and ROS 2. It is our platform for research in human-centered robotics, perception-driven manipulation, and immersive human-robot interaction.

Accessories (3)
  • X-Arm Gripper · UFACTORY
  • X-Arm Camera Stand · UFACTORY
  • Gemini 335 Depth Camera · Orbbec

Dobot Magician Robotic Arm

Desktop Robot Arm

Dobot Magician Robotic Arm

Description

A 4-axis desktop robot arm for teaching, with a 500 g payload, 320 mm reach, and ±0.2 mm repeatability. The lab has ten units, enough for a full class lab. Students swap its tools to pick and place with suction or a gripper, write and draw, and 3D print, and program it in blocks or Python.

Accessories (1)
  • Standard Edition Tool Kit · Dobot

Clearpath Husky A300 with Robot Arm

Mobile Manipulator

Clearpath Husky A300 with Robot Arm

Description

A rugged, all-terrain unmanned ground vehicle (UGV) for autonomous mobile robotics research: IP54-rated, up to 2 m/s, and able to climb 30° grades, running ROS 2 Jazzy. With a robot arm on its top plate, the platform supports mobile manipulation tasks that combine navigation and object interaction in complex environments.

Accessories (2)
  • Gen3 lite Robot Arm · Kinova
  • RealSense D435 Depth Camera · Intel

Clearpath TurtleBot 4

Mobile Robot

Clearpath TurtleBot 4

Description

A ROS 2 mobile robot for education and research, built on the iRobot Create 3 base with a Raspberry Pi 4B on board. It maps its surroundings, navigates autonomously, and runs AI models on its camera, with a 9 kg payload and 2.5–4 hours of operation per charge.

Accessories (2)
  • OAK-D Pro Camera · Luxonis
  • RPLIDAR A1M8 · Slamtec

Virtualis MotionVR Station

XR station

Virtualis MotionVR Station

Description

An advanced balance assessment and rehabilitation platform that integrates a 360-degree dynamic force plate with immersive virtual reality. The system enables precise evaluation of human balance and postural control through Computerized Dynamic Posturography (CDP), including standardized tests such as the Sensory Organization Test (SOT), Limits of Stability (LoS), and the Adaptation Test (ADT).

Varjo VR-3

XR Headset

Varjo VR-3

Description

A tethered PC VR headset built for ultra-high-fidelity immersive experiences, with a 115° field of view and human-eye resolution at the center of view. Its integrated 200 Hz eye tracking enables highly realistic rendering and detailed analysis of where users look.

HTC VIVE Pro

XR Headset

HTC VIVE Pro

Description

A tethered PC VR headset tracked by SteamVR base stations, with 1440 × 1600 pixels per eye, a 90 Hz refresh rate, and a 110° field of view. Paired with VIVE Trackers, it brings real objects and body movement into VR for interaction and motion-tracking studies.

Accessories (1)
  • VIVE Tracker (3.0) · HTC

Meta Quest 3 & 3S

XR Headset

Meta Quest 3 & 3S

Description

The Meta Quest 3 and Quest 3S are standalone mixed reality headsets that support both fully immersive VR and passthrough-based AR experiences. With inside-out tracking and wireless operation, they provide a flexible and accessible platform for developing and deploying interactive XR applications.

Orbbec Astra+ 3D Camera

Depth Camera

Orbbec Astra+ 3D Camera

Description

A structured-light RGB-D camera for indoor scenes, with stable depth from 0.6 to 8 m, precision within 0.3% at 1 m, and 1080p color. The lab has three units. It suits fixed, indoor setups such as watching a workspace or a robot cell from a stand.

Orbbec Gemini 335L

Depth Camera

Orbbec Gemini 335L

Description

An IP65-rated stereo depth camera with a 95 mm baseline, working indoors or outdoors with an optimal depth range of 0.25 to 6 m and a built-in IMU. Its wide 90° depth field of view and rugged housing suit cameras mounted on mobile robots and arms.