The team suggests that houses are just the start.
“The practical applications of PIGINet are not confined to households,” says PhD student, Zhutian Yang. “Our future aim is to further refine PIGINet to suggest alternate task plans after identifying infeasible actions, which will further speed up the generation of feasible task plans without the need of big datasets for training a general-purpose planner from scratch. We believe that this could revolutionize the way robots are trained during development and then applied to everyone’s homes.”
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TechCrunch