ROBOTNESS
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Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning

Merve Atasever, Keyan Azbijari, Cagan Bakirci, Bo-Ruei Huang, Tolga Izdas, Zahra Shahrooei, Richard Yang, Erdem Biyik, Jyotirmoy V. Deshmukh
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Aus dem Abstract

Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched demonstrations. A central challenge is deciding what information should be transferred from the video to the robot.

Aus dem Abstract. Unsere Zusammenfassung folgt.