Immersive Design
Elitebox: A Boxing Training in VR
EliteBox is a VR boxing trainer that combines adaptive AI with immersive combat mechanics for a gamified fitness experience.
Year :
2024
Industry :
VR
Client :
Academic Project
Project Duration :
6 weeks
OVERVIEW:
EliteBox is an immersive VR fitness application designed to simulate professional boxing training using AI-driven opponents. The goal was to combine realistic motion, adaptive AI, and immersive interaction design to create a holistic, gamified boxing workout experience.
THE CHALLENGE:
Traditional home workouts often lack motivation and engagement. Most VR fitness games focus on rhythm rather than combat realism. EliteBox addresses this by introducing a dynamic AI opponent, realistic boxing mechanics, and progressive training modes — all within an immersive virtual ring.
FEATURES:
Realistic Combat Mechanics
Responsive punch tracking (jab, hook, uppercut)
AI opponent with blocking, dodging, and counterattacks
Combo streaks, dodge-and-strike reactions
Adaptive AI
Built using a Finite State Machine
Analyzes player's performance and adjusts difficulty in real-time
Adds realism through AI behavior variability
Game Modes
Combo Practice
Reflex Training
Timed Rounds (3, 5, 10 mins)
Sound & Feedback
Impact-driven SFX, crowd ambiance
Haptic feedback simulating glove force
TOOLS USED:
Tool | Purpose |
|---|---|
Unreal Engine | Game development engine |
Blender | 3D modeling (boxing ring, gloves) |
Meta Quest 2 & Pro | Testing platform (native build) |
Figma | UI wireframes & HUD elements |
EXPERIENCE DESIGN:
VR-first UX with minimal UI clutter
Center-based ring experience for immersion
Visual feedback through stamina bars and AI reaction cues
Designed with motion tracking for realism and comfort
OUTCOME:
Fully functional prototype tested on Meta Quest 2 and pro
Demonstrated proof of concept for a fitness + gaming hybrid product
Learned to balance immersion, performance, and accessibility
Opened new pathways for XR fitness integrations like multiplayer, progress analytics, and voice coaching
Adaptive AI Opponents – Smarter, progressively challenging virtual fighters.
Custom Training Modules – Personalized combos and stamina-focused drills.
Fitness Tracking Integration – Sync with wearables for real-time performance insights.
Multiplayer Mode – Spar with friends or compete on global leaderboards.
AR Expansion – Train in real-world spaces using augmented reality overlays.
More Projects
Immersive Design
Elitebox: A Boxing Training in VR
EliteBox is a VR boxing trainer that combines adaptive AI with immersive combat mechanics for a gamified fitness experience.
Year :
2024
Industry :
VR
Client :
Academic Project
Project Duration :
6 weeks
OVERVIEW:
EliteBox is an immersive VR fitness application designed to simulate professional boxing training using AI-driven opponents. The goal was to combine realistic motion, adaptive AI, and immersive interaction design to create a holistic, gamified boxing workout experience.
THE CHALLENGE:
Traditional home workouts often lack motivation and engagement. Most VR fitness games focus on rhythm rather than combat realism. EliteBox addresses this by introducing a dynamic AI opponent, realistic boxing mechanics, and progressive training modes — all within an immersive virtual ring.
FEATURES:
Realistic Combat Mechanics
Responsive punch tracking (jab, hook, uppercut)
AI opponent with blocking, dodging, and counterattacks
Combo streaks, dodge-and-strike reactions
Adaptive AI
Built using a Finite State Machine
Analyzes player's performance and adjusts difficulty in real-time
Adds realism through AI behavior variability
Game Modes
Combo Practice
Reflex Training
Timed Rounds (3, 5, 10 mins)
Sound & Feedback
Impact-driven SFX, crowd ambiance
Haptic feedback simulating glove force
TOOLS USED:
Tool | Purpose |
|---|---|
Unreal Engine | Game development engine |
Blender | 3D modeling (boxing ring, gloves) |
Meta Quest 2 & Pro | Testing platform (native build) |
Figma | UI wireframes & HUD elements |
EXPERIENCE DESIGN:
VR-first UX with minimal UI clutter
Center-based ring experience for immersion
Visual feedback through stamina bars and AI reaction cues
Designed with motion tracking for realism and comfort
OUTCOME:
Fully functional prototype tested on Meta Quest 2 and pro
Demonstrated proof of concept for a fitness + gaming hybrid product
Learned to balance immersion, performance, and accessibility
Opened new pathways for XR fitness integrations like multiplayer, progress analytics, and voice coaching
Adaptive AI Opponents – Smarter, progressively challenging virtual fighters.
Custom Training Modules – Personalized combos and stamina-focused drills.
Fitness Tracking Integration – Sync with wearables for real-time performance insights.
Multiplayer Mode – Spar with friends or compete on global leaderboards.
AR Expansion – Train in real-world spaces using augmented reality overlays.
More Projects
Immersive Design
Elitebox: A Boxing Training in VR
EliteBox is a VR boxing trainer that combines adaptive AI with immersive combat mechanics for a gamified fitness experience.
Year :
2024
Industry :
VR
Client :
Academic Project
Project Duration :
6 weeks
OVERVIEW:
EliteBox is an immersive VR fitness application designed to simulate professional boxing training using AI-driven opponents. The goal was to combine realistic motion, adaptive AI, and immersive interaction design to create a holistic, gamified boxing workout experience.
THE CHALLENGE:
Traditional home workouts often lack motivation and engagement. Most VR fitness games focus on rhythm rather than combat realism. EliteBox addresses this by introducing a dynamic AI opponent, realistic boxing mechanics, and progressive training modes — all within an immersive virtual ring.
FEATURES:
Realistic Combat Mechanics
Responsive punch tracking (jab, hook, uppercut)
AI opponent with blocking, dodging, and counterattacks
Combo streaks, dodge-and-strike reactions
Adaptive AI
Built using a Finite State Machine
Analyzes player's performance and adjusts difficulty in real-time
Adds realism through AI behavior variability
Game Modes
Combo Practice
Reflex Training
Timed Rounds (3, 5, 10 mins)
Sound & Feedback
Impact-driven SFX, crowd ambiance
Haptic feedback simulating glove force
TOOLS USED:
Tool | Purpose |
|---|---|
Unreal Engine | Game development engine |
Blender | 3D modeling (boxing ring, gloves) |
Meta Quest 2 & Pro | Testing platform (native build) |
Figma | UI wireframes & HUD elements |
EXPERIENCE DESIGN:
VR-first UX with minimal UI clutter
Center-based ring experience for immersion
Visual feedback through stamina bars and AI reaction cues
Designed with motion tracking for realism and comfort
OUTCOME:
Fully functional prototype tested on Meta Quest 2 and pro
Demonstrated proof of concept for a fitness + gaming hybrid product
Learned to balance immersion, performance, and accessibility
Opened new pathways for XR fitness integrations like multiplayer, progress analytics, and voice coaching
Adaptive AI Opponents – Smarter, progressively challenging virtual fighters.
Custom Training Modules – Personalized combos and stamina-focused drills.
Fitness Tracking Integration – Sync with wearables for real-time performance insights.
Multiplayer Mode – Spar with friends or compete on global leaderboards.
AR Expansion – Train in real-world spaces using augmented reality overlays.