What is AgiBot Digital World
AgiBot Digital World is a high-fidelity robot simulation framework launched by AgiBot, providing efficient support for research and applications of robot manipulation skills. AgiBot Digital World integrates massive realistic 3D assets, diverse expert trajectory generation mechanisms, and comprehensive model evaluation tools. Based on high-fidelity simulation and full-chain automated data generation, it rapidly builds diverse robot training scenarios. The framework is developed based on NVIDIA Isaac-Sim, featuring highly realistic visual rendering and precise physical simulation, supporting multimodal large model-driven automatic generation of tasks and scenarios, and combining domain randomization and data augmentation techniques to generate high-quality, diverse expert trajectory data and enhance model generalization ability. AgiBot also open-sources the AgiBot Digital World Dataset, covering 5 major categories of scenarios, 180+ object categories, 9 materials, and 12 core skills, contributing to the development of the global embodied intelligence robotics field.
Main Features of AgiBot Digital World
- High-Fidelity Simulation Training Scenarios：
- Multi-Source High-Quality 3D Assets: Generated based on manual modeling, 3D reconstruction technology, and generative artificial intelligence (AIGC), meeting the simulation needs of complex tasks.
- Realistic Perception and Interaction Details: Developed based on the NVIDIA Isaac-Sim platform, providing realistic visual and physical interaction effects.
- Automatic Generation of Tasks and Scenarios: Supports automatic generation of manipulation tasks and scene layouts based on the asset library, adapting to different training needs.
- Full-Chain Automated Data Generation：
- Diversified Expert Trajectory Generation Strategies: Including real-machine operation digital twins, automatic generation by embodied agents, and simulated teleoperation.
- Domain Randomization and Data Augmentation: By adjusting lighting, materials, physical properties, etc., generates diverse data and enhances model generalization ability.
- Automated Generation of Large-Scale DataCollection: Supports multimodal data generation and rapidly builds large-scale expert trajectory data.
- Open-Source Massive Simulation Data: The dataset covers 5 major categories of scenarios, 180+ object categories, 9 materials, and 12 core skills. The data features high quality, rapid generalization, diverse tasks, and flexible application, supporting multi-skill training and multi-task generalization execution.
Technical Principles of AgiBot Digital World
- Development Based on NVIDIA Isaac-Sim: Based on the high-performance simulation platform NVIDIA Isaac-Sim, it achieves highly realistic visual rendering and precise physical simulation. Using GPU acceleration and real-time simulation technology, it ensures efficient operation of the simulation environment.
- Multimodal Large Model-Driven: Combines multimodal large models (such as vision and language models) to automatically generate tasks and scene layouts. Based on the generalization ability of large models, it flexibly generates diverse robot manipulation tasks and environments.
- Expert Trajectory Generation and Data Augmentation: Multiple strategies such as real-machine operation digital twins, automatic generation by embodied agents, and simulated teleoperation generate expert trajectory data. Combined with domain randomization and data augmentation techniques (such as randomization of lighting, materials, and physical properties), it enhances data diversity and model generalization ability.
- Automated Task and Scenario Generation: Based on the asset library and multimodal large models, automatically generate operation tasks and scene layouts according to user needs. Support one-click task switching and automatic supplementation of missing objects, enabling a data loop.
AgiBot Digital World project address
- Project official website：https://agibot-digitalworld.cn/
- HuggingFace model library：https://huggingface.co/datasets/agibot-world/AgiBotDigitalWorld
Application scenarios of AgiBot Digital World
- Robot skill training: Based on a high-fidelity simulation environment, quickly pre-train robot operation skills, such as grasping and transporting, reducing training costs in real environments.
- Algorithm development and testing: Provides a complete process from trajectory generation to model validation, accelerating the development and optimization of robot algorithms.
- Industrial automation: Simulate industrial scenarios, optimize the efficiency and precision of robots on production lines, and reduce deployment risks.
- Service robot development: In scenarios such as homes, supermarkets, and restaurants, train robots to complete cleaning, organizing, and service tasks, improving user experience.
- Artificial intelligence research and education: As a research and education tool, it supports research in fields such as embodied intelligence and reinforcement learning, providing rich open-source resources.