Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection

• URL: http://arxiv.org/abs/2412.04455v2
• Date: Mon, 09 Dec 2024 16:07:24 GMT
• Title: Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection
• Authors: Enshen Zhou, Qi Su, Cheng Chi, Zhizheng Zhang, Zhongyuan Wang, Tiejun Huang, Lu Sheng, He Wang,
• Abstract summary: We propose Code-as-Monitor (CaM) for both open-set reactive and proactive failure detection. To enhance the accuracy and efficiency of monitoring, we introduce constraint elements that abstract constraint-related entities. Experiments show that CaM achieves a 28.7% higher success rate and reduces execution time by 31.8% under severe disturbances.
• Score: 56.66677293607114
• License:
• Abstract: Automatic detection and prevention of open-set failures are crucial in closed-loop robotic systems. Recent studies often struggle to simultaneously identify unexpected failures reactively after they occur and prevent foreseeable ones proactively. To this end, we propose Code-as-Monitor (CaM), a novel paradigm leveraging the vision-language model (VLM) for both open-set reactive and proactive failure detection. The core of our method is to formulate both tasks as a unified set of spatio-temporal constraint satisfaction problems and use VLM-generated code to evaluate them for real-time monitoring. To enhance the accuracy and efficiency of monitoring, we further introduce constraint elements that abstract constraint-related entities or their parts into compact geometric elements. This approach offers greater generality, simplifies tracking, and facilitates constraint-aware visual programming by leveraging these elements as visual prompts. Experiments show that CaM achieves a 28.7% higher success rate and reduces execution time by 31.8% under severe disturbances compared to baselines across three simulators and a real-world setting. Moreover, CaM can be integrated with open-loop control policies to form closed-loop systems, enabling long-horizon tasks in cluttered scenes with dynamic environments.

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