2025
Multimodal Task Attention Residual Reinforcement Learning: Advancing Robotic Assembly in Unstructured Environment
RA-L 2025
Robotic assembly in dynamic and unstructured environments poses challenges for recent methods, due to background noise and wide-ranging errors. Directly learning from environments relies on complex models and extensive training iterations to adapt. Representation selection approaches, which depend o