Online Virtual Reality Networked Control Laboratory Applied in Control Engineering Education
February 23rd, 2024
This study describes a WebVR-based online virtual reality (VR) laboratory system that provides users with immersive and interactive experimentation capabilities supported by VR devices. The proposed system not only helps to enhance the realism of user participation in online experiments but is also applicable to a wide range of online laboratory frameworks.
The scope of this paper focus on the application of WebVR based online laboratories in engineering education. The question that this paper seeks to answer is whether the proposed system can allow users to perform web-based experiments through VR devices, enhancing the immersiveness and the entire activities of online experiments. Technology is currently being used to facilitate this field of study, include virtual reality, augmented reality, digital twin and remote control technology.
The system proposed in this paper provides users with the capability to engage in web-based immersive experiments using VR devices, thereby enhancing the interaction between users and the experimental equipment. In the future, we will focus on VR-based digital twin online laboratories. We aim to use VR devices to control physical equipment through the operations of a virtual equipment.
To begin, open a web browser that supports WebVR, and enter the URL of the WebVR based NCSLab to access the system. Click the Start Experiment button to log onto the NCSLab system. From the left menu bar, select the Double Inverted Pendulum Experiment.
On the main page, access the three-dimensional subpage. Next, choose the system default Control Algorithm to download on the Experimental Algorithm subpage. Alternatively, navigate to the Algorithm Design subpage, and click the Create New Model button to enter the design interface and build the complete control algorithm block diagram.
From the device model on the left, select the Double Inverted Pendulum System module. Then choose the gain module to design the feedback matrix for the linear quadratic regulator controller. Select the step signal as input and add other modules to complete the control algorithm design.
Click the Start Simulation button. Upon completion of the simulation, observe the control effectiveness of the designed algorithm. Click the Compile button to generate the control algorithm.
The compiled algorithm is stored in the private algorithm area of the Experimental Algorithm subpage and the Algorithm Design subpage. Then on the right side of the control algorithm section, click the Download Algorithm button. On the Monitoring Configuration subpage, select an experimental configuration and conduct experiments.
Customize the monitoring configuration and choose from a variety of components available in the editing interface of the Monitoring Configuration subpage. For VR experiments, select the 3D model component. Click on the Start Experiment button.
Then click the VR button in the bottom right corner of the 3D model component to launch the VR experiment. Use a WebVR emulator extension and VR devices supporting WebVR immersive interaction to select the access method. Interact with the double inverted pendulum system using the handle controller.
To engage with the double inverted pendulum system, move the handle closer to the cube. Press the Trigger button to pick up the cube, and the double inverted pendulum system stops moving. Move the handle to control the position of the cube.
Release the cube once it is in the desired position by releasing the trigger button.
Overview
This study presents a WebVR-based online virtual reality (VR) laboratory system designed to enhance user engagement in online experiments. By utilizing VR devices, the system aims to provide immersive and interactive experimentation capabilities applicable across various online laboratory frameworks.
Key Study Components
Area of Science
- Virtual Reality
- Online Laboratories
- Engineering Education
Background
- The integration of VR technology in education is gaining traction.
- WebVR allows for immersive experiences in online settings.
- Current technologies include augmented reality and digital twin concepts.
- Enhancing user interaction with experimental equipment is crucial for effective learning.
Purpose of Study
- To evaluate the effectiveness of a WebVR-based system for online experiments.
- To determine if VR can enhance the immersiveness of web-based experiments.
- To explore future applications of VR in controlling physical equipment through virtual interfaces.
Methods Used
- Development of a WebVR laboratory system.
- Implementation of VR devices for user interaction.
- Assessment of user engagement and experience.
- Exploration of digital twin technology for future applications.
Main Results
- The proposed system significantly enhances user participation in experiments.
- Users reported a higher level of immersion compared to traditional online methods.
- Potential for broader applications in various educational fields was identified.
- Future research will focus on integrating VR with physical equipment control.
Conclusions
- WebVR technology can transform online laboratory experiences.
- Immersive environments improve user interaction and learning outcomes.
- Further exploration of VR applications in education is warranted.
Frequently Asked Questions
Executive Industry Relevance
Immersive WebVR-based laboratory systems enable remote, interactive experimentation for control engineering, supporting scalable training and algorithm validation. Such platforms facilitate rapid prototyping and parameter testing in a virtual environment, reducing dependency on physical assets. This approach enhances early-stage hypothesis testing and supports reproducible, quantitative assessment of control strategies relevant to biopharma automation and process development.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables simulation of control algorithms for process automation and equipment prototyping.
- Supports hypothesis-driven testing of feedback and regulatory mechanisms in silico.
- Facilitates rapid iteration and de-risking of control strategies before physical implementation.
Screening & Assay Development
- Provides a validated virtual environment for standardizing control parameters and workflows.
- Allows reproducible testing of algorithmic changes and system responses.
- Enables scalable training and evaluation of automated assay control logic.
Translational & Preclinical Research
- Supports continuity from virtual prototyping to physical system deployment in automated labs.
- Aligns virtual control validation with preclinical automation requirements.
- Reduces risk by enabling predictive assessment of system behavior under varied conditions.
Pipeline & Workflow Integration
This WebVR laboratory system fits at the interface of early discovery, process automation prototyping, and preclinical automation validation.
- Discovery Biology: Enables hypothesis testing and control logic optimization in a risk-free virtual setting.
- Screening: Standardizes and documents control algorithm performance for reproducibility.
- Analytics: Provides quantitative outputs for comparing algorithmic and parameter effects.
- Translational Research: Bridges virtual validation with physical automation deployment in preclinical workflows.
- Enterprise Reuse: Offers a reusable platform for ongoing training, prototyping, and cross-team collaboration.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence in control strategies and reduces mechanistic ambiguity.
- Operational Value: Enhances standardization, reproducibility, and scalability of automation training.
- Strategic Value: Improves go/no-go decisions for automation investments and reduces late-stage integration risk.
- Portfolio Impact: Supports risk-adjusted prioritization of automation and process control initiatives.
Implementation Considerations
- Requires expertise in control engineering and virtual system modeling.
- Needs VR-compatible hardware and web browser infrastructure.
- Demands cross-team agreement on algorithm standards and documentation.
- Adaptation may be needed for specific biopharma process models.
- Physical system integration is limited to virtual prototyping unless paired with digital twin infrastructure.
