Reproduce “Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Koffivi Fidèle Gbagbe, Miguel Altamirano Cabrera, Ali Alabbas, Oussama Alyunes, Artem Lykov, Dzmitry Tsetserukou
Bi-VLA, developed by the Intelligent Space Robotics Laboratory at Skoltech, is a vision-language-action model system for bimanual robotic dexterous manipulations that interprets natural language instructions and visual inputs to orchestrate coordinated dual-arm actions. The system achieves 100% success in code generation from language commands and up to 83.4% task execution success for bimanual tasks like salad preparation.
Key insights
- Large Language Models can effectively serve as high-level semantic planners and code generators for orchestrating complex, coordinated bimanual robotic actions from natural language instructions.
- Robust visual perception and accurate 2D to 3D coordinate conversion are critical bottlenecks and direct determinants of overall task execution success in vision-language-action systems.
- A modular architecture integrating LLMs for planning and VLMs for perception allows for a less data-intensive approach to bimanual tasks, bridging high-level cognition and low-level control.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.