From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation

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• PRIMO R1 transforms video MLLMs from passive observers to active critics by leveraging outcome-based Reinforcement Learning for explicit Chain-of-Thought generation.method 70%
• PRIMO R1 achieves state-of-the-art performance across diverse in-domain environments and out-of-domain real-world humanoid scenarios.result 70%
• PRIMO R1's 7B model achieves a 50% reduction in the mean absolute error compared to specialized reasoning baselines.result 70%
• PRIMO R1 establishes state-of-the-art performance on the RoboFail benchmark with 67.0% accuracy, surpassing OpenAI o1 by 6.0%.result 70%
• PRIMO R1 exhibits strong zero-shot generalization on difficult failure detection tasks.result 70%
• The proposed PRIMO R1 framework requires high-quality video and state image inputs, which may be costly to implement.limitation 70%
• The product opportunity is targeted at manufacturing companies with automated assembly lines to reduce defect rates and downtime.market 70%

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