Reboverse Simulation Engine
Reboverse: A Unified Framework built on Roboverse
Last updated
Reboverse: A Unified Framework built on Roboverse
Last updated
Reboverse is Reborn’s advanced simulation engine, designed to facilitate the training and evaluation of embodied AI models, built upon the famous Roboverse. By leveraging the capabilities of the RoboVerse framework, Reboverse offers a comprehensive environment that supports diverse robotic embodiments and tasks, ensuring seamless transitions between simulation and real-world applications.
Key Features:
MetaSim Integration: At the core of Reboverse is MetaSim, a unified infrastructure that abstracts various simulation environments into a universal interface. This allows for consistent configuration and control across different simulators, enhancing interoperability and extensibility.
High-Fidelity Synthetic Dataset: Reboverse provides a large-scale, high-quality synthetic dataset constructed through multiple approaches, including migration from public datasets, policy rollouts, and motion planning, all enhanced by data augmentation techniques.
Standardized Benchmarks: To ensure consistent evaluation, Reboverse includes unified benchmarks for both imitation learning and reinforcement learning, enabling assessments across different levels of generalization.
Multimodal Sensor Simulation: The platform supports the simulation of various sensor modalities, including RGB, depth, LiDAR, tactile, and proprioceptive sensors, facilitating comprehensive multimodal training.
Open-Source Collaboration: Reboverse is open-sourced, encouraging contributions from the community to expand its capabilities and adapt to emerging research needs.
By integrating these features, Reboverse serves as a pivotal tool in Reborn's mission to develop scalable and generalizable robotic foundation models, bridging the gap between simulation and real-world deployment.
[1] Roboverse:
