RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins
Yao Mu, Tianxing Chen, Zanxin Chen, Shijia Peng, Zhiqian Lan, Zeyu Gao, Zhixuan Liang, Qiaojun Yu, Yude Zou, Mingkun Xu, Lunkai Lin, Zhiqiang Xie, Mingyu Ding, Ping Luo·April 17, 2025
Summary
RoboTwin is a generative framework for dual-arm robotics, using 3D models & large language models to create realistic scenarios & datasets. It surpasses models trained solely on real-world data, offering a benchmark with simulated and real-world data. Robotic advancements focus on real-time language interaction, scalable supervision, imitation learning, and multimodal code generation.
Introduction
Background
Overview of dual-arm robotics
Importance of generative frameworks in robotics
Objective
Aim of RoboTwin in enhancing dual-arm robotic capabilities
Benefits of using 3D models and large language models
Method
Data Collection
Sources of data for training RoboTwin
Integration of simulated and real-world datasets
Data Preprocessing
Techniques for preparing data for the generative model
Handling of 3D models and language data
Model Architecture
Description of the generative framework
Components of RoboTwin and their functions
Training Process
Methodology for training the model
Optimization techniques and hyperparameter tuning
Applications
Real-Time Language Interaction
Implementation of natural language processing in robotics
Enhancing human-robot collaboration
Scalable Supervision
Dynamic adjustment of supervision levels
Adaptability to varying robotic tasks
Imitation Learning
Learning from human demonstrations
Transfer of skills to new robotic tasks
Multimodal Code Generation
Generation of code for robotic actions
Integration of visual and textual inputs
Evaluation
Benchmarking
Comparison with models trained on real-world data
Metrics for assessing performance and realism
Case Studies
Detailed examples of RoboTwin in action
Analysis of outcomes and improvements over existing methods
Conclusion
Future Directions
Potential advancements in dual-arm robotics
Ongoing research and development in RoboTwin
Impact
Expected impact on robotics industry and applications
Societal benefits and ethical considerations
Basic info
papers
computation and language
robotics
artificial intelligence
Advanced features
Insights
How does the RoboTwin framework integrate 3D models and large language models to enhance dual-arm robotics?
In what ways does RoboTwin ensure compatibility between simulated and real-world data for benchmarking?
What are the key implementation strategies used in RoboTwin for real-time language interaction and scalable supervision?
What innovative approaches does RoboTwin employ in imitation learning and multimodal code generation?