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Video2STL is presented, a framework that converts observation-only videos into parametric Signal Temporal Logic (STL) specifications and uses the resulting formal representation for robot learning, and supports cross-embodiment transfer from human or animal videos to robot control.
This study presents a comparative case study of representative motion planning methods drawn from major benchmark ecosystems, including CARLA, nuPlan, and the Waymo Open Dataset to highlight the strengths and weaknesses of current approaches.
This work studies whether large language models (LLMs) can fill this gap by generating Parametric Signal Temporal Logic (PSTL) specifications that are subsequently used for policy learning, and instantiate the parameters of the generated PSTL templates using expert trajectories and retain only specifications that are c...
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