ForceVLA2: Unleashing Hybrid Force-Position Control with Force Awareness for Contact-Rich Manipulation

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• ForceVLA2 is an end-to-end vision-language-action framework that enables hybrid force-position control and explicit force awareness for robots.method 95%
• ForceVLA2 introduces force-based prompts into the VLM expert to construct force-aware task concepts.method 95%
• ForceVLA2 employs a Cross-Scale Mixture-of-Experts (MoE) in the action expert to adaptively fuse task concepts with real-time interaction forces.method 95%
• The ForceVLA2-Dataset contains 1,000 trajectories across 5 contact-rich tasks, including multi-view images, task prompts, proprioceptive state, and force signals.method 95%
• ForceVLA2 improves success rates and reliability in contact-rich manipulation, outperforming pi0 by 48.0% and pi0.5 by 35.0% across 5 tasks.result 95%
• ForceVLA2 mitigates common failure modes such as arm overload and unstable contact.result 90%
• The limited dataset size of 1,000 trajectories may not generalize to all real-world tasks.limitation 85%
• The product's go-to-market strategy includes targeting industrial automation trade shows and partnering with robotic arm manufacturers.market 90%

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