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Vrtron

In development · AI & Avatars · Engine

Bvatar

Real-time procedural avatar engine. Context-tagged motion knowledge base distilled from teacher models, skeleton-agnostic retargeting, joint-masked layering of locomotion, speech-gesture and face. Powers walk-and-talk for embodied AI.

year
2025–2026
role
Concept, engineering, research
scope
Engine · Powers TOW NPCs and Borromini Kiosk

01 · Overview

Bvatar is Vrtron's internal avatar engine: a real-time, procedural system for embodied AI characters that can locomote, gesture, look, and speak in plausible combination.

At its heart is a context-tagged motion knowledge base built by distilling teacher models, plus a skeleton-agnostic retargeting layer so the same motions drive different character rigs without per-character authoring. Locomotion, speech-gesture and face are independent layers that combine through joint-masked blending.

Bvatar powers walk-and-talk behaviour in TOW's NPC framework and the Borromini Kiosk, and is the reference runtime for the Vrtron Avatar product (separately developed for client work).

02 · Highlights

Features in development

01

Joint-masked layering

Locomotion, speech-gesture and face combine via per-joint masking so a character can walk and talk at the same time without one motion fighting the other.

02

Skeleton-agnostic retargeting

ZeroEGGS / SMPL-X / Ubisoft BVH round-trips handled in-engine. Round-trip MAE ~0.69 cm at body scale.

03

Context-tagged motion KB

Motions are tagged with the context that produced them (intent, prosody, scene), so the engine can sample the right gesture for the right moment.

04

Teacher-model distillation

Large generative teacher models capture the motion space; Bvatar runs the distilled student fast enough for real-time on consumer GPUs.

03 · Stack

Made with