Specification-Aware Distribution Shaping for Robotics Foundation Models
Specification-Aware Distribution Shaping for Robotics Foundation Models
This paper introduces a specification-aware action distribution optimization framework designed to enforce Signal Temporal Logic (STL) constraints during the execution of pretrained robotics foundation models. The method computes minimally modified action distributions at each decision step to satisfy hard STL feasibility constraints by reasoning over the remaining horizon using forward dynamics propagation, without altering the model's parameters. The framework is validated in simulation using state-of-the-art robotics foundation models across multiple environments and complex specifications.
The authors propose a framework to enforce Signal Temporal Logic constraints on pretrained robotics foundation models without parameter modification, validated in simulation.
Source: arXiv Robotics — research abstracts · Read original article ↗
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on distribution that satisfies a hard STL feasibility constraint by reasoning over the remaining horizon using forward dynamics propagation. We validate the proposed framework in simulation using state-of-the-art robotics foundation models across multiple environments and complex specifications.
Open source S4
arXiv:2603.17969v2 Announce Type: replace Abstract: Robotics foundation models have demonstrated strong capabilities in executing natural language instructions across diverse tasks and environments. However, they remain largely data-driven and lack formal guarantees on constraint satisfaction during deployment. In practice, robots often need to comply with operational constraints involving rich spatio-temporal requir
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Source：arXiv Robotics — research abstracts · arxiv.org