GAS-Robo: Converting Scene Into a Grid-Action Space for LLM-Driven Open-Ended Robotic Manipulation
Generalizing to out-of-distribution scenarios remains a major challenge for traditional robotic manipulation methods trained on closed datasets. Recent approaches leveraging foundation models have significantly improved zero-shot capabilities by utilizing vision-language models, yet many of these methods treat the foun...