PACER: Process-Aware VLA Policy Learning from Human Corrections for Robotic Disassembly
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초록 발췌
Robotic disassembly of end-of-life (EoL) products requires robots to accommodate product variation, follow prerequisite sequences, and approach components precisely for contact-rich manipulation. Supervised fine-tuning (SFT) provides a practical path for adaptation, but limited and costly disassembly data cannot capture the distribution shifts arising from changing environments and product uncertainties.
초록에서 가져왔습니다. 요약을 준비 중입니다.