OVITA uses LLM-generated Python code, a QP safety module, and user feedback to adapt robot trajectories from open-vocabulary natural language instructions, with an 81.4% user-study success rate.
Llm-planner: Few-shot grounded planning for embodied agents with large language models,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
OVITA: Open-Vocabulary Interpretable Trajectory Adaptations
OVITA uses LLM-generated Python code, a QP safety module, and user feedback to adapt robot trajectories from open-vocabulary natural language instructions, with an 81.4% user-study success rate.