4DSynth: Controllable Procedural World Synthesis for Dynamic Embodied Simulation
Not on the map. Why?
Abstract (arXiv)
Embodied agents need environments that are visually diverse, physically interactive, and changing over time. Procedural simulators can generate large interactive scene collections, and recent 4D generators produce compelling visual dynamics. Combining these properties in one environment, however, still demands extensive manual effort, and the result is rarely editable or controllable enough to reuse at scale. We present 4DSynth, a controllable procedural system that turns a natural-language description, a blueprint mask, or a single photograph into an editable 4D environment with explicit geometry, animated actors, collision-free trajectories, and physics-ready simulation state. Multiple scene routes share one geometry-grounded representation, so the same pipeline handles animation, camera planning, rendering, and task generation. To validate the full pipeline, we construct 4DSynth-Nav, an interactive navigation benchmark generated entirely from 4DSynth's procedural scenes. Two vision-language models evaluated across three difficulty tiers both fail the majority of tasks and stall after early subtasks. The same procedural controllability that produces these environments also makes each failure reproducible and each difficulty axis independently tunable. This paper presents both a controllable generation pipeline and the scalable benchmark it enables, offering a practical foundation for developing and evaluating embodied agents.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 18 references that are in the map. First posted on arXiv 27 Aug 2026.
Builds on
16 of 18 references.
References · 16
- 2025Qwen3-VL Technical Reportcited by 2,793
- 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
- 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 869
- 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 692
- 2020SAPIEN: A SimulAted Part-based Interactive ENvironmentcited by 595
- 2022ProcTHOR: Large-Scale Embodied AI Using Procedural Generationcited by 380
- 2023Holodeck: Language Guided Generation of 3D Embodied AI Environmentscited by 268
- 2025SAM 3D: 3Dfy Anything in Imagescited by 247
- 2023Habitat 3.0: A Co-Habitat for Humans, Avatars and Robotscited by 228
- 2021iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Taskscited by 194
- 20234D-fy: Text-to-4D Generation Using Hybrid Score Distillation Samplingcited by 185
- 2023Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Modelscited by 169
4 more
- 2023Infinite Photorealistic Worlds using Procedural Generationcited by 147
- 2024Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generationcited by 137
- 2024Automated Creation of Digital Cousins for Robust Policy Learningcited by 91
- 2026Vision-as-Inverse-Graphics Agent via Interleaved Multimodal Reasoningcited by 49
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2026SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation
- 2026Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation
- 2026GS-Agent: Creating 4D Physical Worlds With Generative Simulation
- 2026Kinema4D: Kinematic 4D World Modeling for Spatiotemporal Embodied Simulation
- 2026Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos
- 20254DWorldBench: A Comprehensive Evaluation Framework for 3D/4D World Generation Models
- 2025Dreamland: Controllable World Creation with Simulator and Generative Models
- 2026Kepler4D: Controllable Future Video Generation via 4D Scene State Evolution