UX-I | Martin Luber

Research

Eyeviation’s VCAT™ (Virtual Cognitive-Aware Trainer) stands out in the VR firearms training market due to its focus on the "cognitive layer"—tracking eye movement and decision-making before the shot is even fired.

Below are five of its closest competitors in the virtual and tech-enhanced firearms training space, followed by a comparative analysis.

Top 5 Competitors ( Pro-military Training )

Operator XR

A highly portable system from Australia used by elite military and special forces. It focuses on using real service weapons converted for VR.

VirTra

A veteran in the industry known for massive, wrap-around projection screens and tetherless VR. They emphasize judgmental use-of-force training and "stress-fire" scenarios.

Apex Officer (Axon)

One of the most widely adopted VR systems for law enforcement in the US, offering a wide range of pre-built scenarios for de-escalation and active shooter response.

V-Armed

Focuses on high-fidelity, large-scale tactical simulations where multiple trainees can move through a 3D space simultaneously using cinematic-quality graphics.

Mantis (MantisX/Laser Academy)

While not a full VR "world" like the others, it is the primary competitor in the data-driven training space. It uses rail-mounted sensors to track muzzle movement with extreme precision.

Summary of Differences:

Innovation: Eyeviation is unique because it measures internal metrics (eye gaze, focus) rather than just external results (where the bullet hit).
Realism: Operator XR leads in hardware realism by letting you use your actual service pistol, whereas VCAT and Apex Officer often use dedicated VR controllers or modified replicas.
Scale: V-Armed and VirTra are better for team-based tactical maneuvers in large rooms, while Eyeviation is optimized for "micro-training" that can be done in a very small footprint.

Top 3 Competitors ( Domestic / Commersial / Sport )

ACE Virtual Shooting

ACE is widely considered the gold standard for competitive pistol shooters. Unlike basic VR games, it uses a dedicated "Handset" that mounts your VR controller onto a weighted frame with a realistic trigger.

Why it’s different: It mimics the exact feel of a competition handgun. It’s built for "dry fire" at home, focusing on high-speed transitions and stage planning.

GAIM

GAIM (developed with Aimpoint) is the leader in virtual hunting. It uses high-end wooden stocks to provide a tactile experience.

Why it’s different: It focuses on "lead"—knowing how far in front of a running boar or flying duck you need to aim. It includes detailed anatomy charts to show where your shot hit the animal's vitals.

Texture VR (Real Stock Pro)

Texture VR is less about the "game" and more about the physical tool. Their Real Stock Pro V3 is an adjustable frame made of real wood and aircraft-grade aluminum.

Why it’s different: It is designed to match the exact weight and balance of your real-world shotgun (up to 10lbs). For a professional clay shooter, this allows for perfect muscle memory transfer to the range.

🎯 Most Common Shooting Targets in the U.S.

These are widely used across civilian ranges, law enforcement, and military training:

1. Silhouette Targets (Humanoid Outline)

Most common for defensive and tactical training
Examples:
- B-27 (law enforcement qualification)
- Simplified human torso shapes
Purpose:
- Center-mass accuracy
- Realistic engagement simulation (non-graphic)

2. Bullseye Targets

Classic circular targets with scoring rings
Used in:
- Precision shooting
- Competitive shooting (e.g., NRA-style)
Purpose:
- Accuracy and grouping

3. Steel Targets (Reactive)

Metal plates that:
- Fall
- Swing
- Make sound on impact
Common shapes:
- Circles
- Silhouettes
Purpose:
- Immediate feedback
- Engagement and speed drills

4. Moving Targets

Slide laterally or pop up/down
Used in:
- Advanced training
Purpose:
- Tracking and reaction time

5. Specialty Training Targets

“Shoot / No-shoot” decision targets
Numbered or colored targets
Purpose:
- Cognitive + reaction training

Top Handguns in the U.S. (Common / Widely Used)

These are among the most popular and widely adopted (civilian + law enforcement influence):

1. Glock 19

Compact 9mm
Extremely widespread (civilian + police)
Known for reliability and simplicity

2. Smith & Wesson M&P Shield

Slim, concealable
Very common for personal use

3. SIG Sauer P320

Modular platform
Basis for U.S. Army sidearm (M17/M18 variant)

Standard U.S. Army Rifles (Assault Rifle Category)

In military terms, these are standard-issue service rifles, not civilian “assault weapons”:

1. M4 Carbine

Primary infantry weapon
Lightweight, versatile
Most common rifle in active service

2. M16 Rifle

Longer variant of M4
Still used in some units and roles

3. M27 Infantry Automatic Rifle

Used by U.S. Marine Corps
More accurate, heavier barrel
Replacing some M4 roles in specific units

Conclusions

VR UX Considerations

This project reinforces that designing for VR requires a different mindset compared to traditional UI:

UI is spatial, not fixed – size is relative to distance from the user
Object placement is critical – poor positioning directly impacts usability and comfort
Interaction must be explicit and forgiving – buttons and dialog elements must be easy to target using raycast or gaze
Proximity affects usability:
- Elements too close → difficult to focus
- Elements at the edge of the field of view → can cause discomfort or dizziness

Overall, VR UI should prioritize:

Clarity
Comfort
Spatial consistency

Design Readiness

At this stage, decisions are no longer based purely on assumptions but are informed by:

Competitive benchmarks
Domain standards (shooting training)
VR interaction constraints

This allows for more grounded and defensible UX decisions moving forward.

Key Questions / Thougts

Core Flow

When does the user choose the weapon and targets?
What is the default training mode?

Customization

Can users create and save custom environments (target setups)?
What level of control does the user have over target configuration?

System Constraints

What is the maximum number of targets allowed per session?
Are all training environments structurally the same, or do they vary?

Guns Logic

Are training scenarios consistent across all weapon types?
How does weapon selection impact environment?
- Does it change difficulty?
- Does it affect target behavior ?

VR UX Validation

How do we validate that UI elements are correctly positioned in 3D space?
Are interaction zones large and accessible enough?
Is the interface comfortably within the user’s field of view?

Workflow Summary

1. Initial Concept

At the start, I envisioned a spatial VR setup where weapon and target selection would take place on a virtual table positioned next to the user.

2. Research & Problem Identification

After reviewing:

VR UX best practices
Spatial interaction constraints
Provided reference materials

I identified two key issues with the initial approach:

a. Usability & Comfort

A side-positioned “table” would require a medium-to-large UI surface
This could push parts of the interface too close to the user, reducing readability and causing discomfort

b. System Consistency

Reference materials indicated an existing in-world screen/panel
Introducing a separate interaction surface (table) would:
- Break consistency
- Add unnecessary cognitive load
- Complicate the flow

3. Direction Shift

Based on these insights, I pivoted to:

Leveraging the existing screen/panel as the primary interaction surface
Aligning UI placement with VR comfort standards (distance, field of view)
Designing the experience as a dialog-driven flow within that panel

This approach:

Improves usability
Maintains spatial consistency
Reduces interaction complexity

4. Content & System Definition

Using research on common firearms and training targets, I defined:

Weapon categories
Target types and training scenarios

5. Exploration with AI Tools

To accelerate ideation, I generated early mockups using:

Figma Make
Google AI Studio
Lovable

From these explorations:

I extracted useful layout patterns and UI ideas
Combined the strongest elements into a unified direction

6. Wireframing & Flow Validation

Created a complete wireframe flow in Figma
Mapped all user interactions:
- Weapon selection
- Target configuration
Ensured:
- Logical navigation
- Coverage of edge cases
- System consistency

FIGMA FLOW LINK

7. Refinement & Spatial Communication

Polished the UI design for clarity and hierarchy
Added supporting visuals to compensate for VR’s 3D nature:
- Dialog placement in space
- Distance and angle considerations
- Interaction zones