A personalized, proactive LLM planner suggests helpful next actions during human-robot lunch packing, reporting 38.7% faster task execution at the cost of an extra 5.6-minute setup phase.
Situated human–robot collaboration: predicting intent from grounded natural language,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
ProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration
A personalized, proactive LLM planner suggests helpful next actions during human-robot lunch packing, reporting 38.7% faster task execution at the cost of an extra 5.6-minute setup phase.