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Training generative motion models with constraints directly integrated into the objective can drastically reduce collision rates and improve trajectory quality in robot navigation tasks.
Robots can nimbly switch between autonomous and teleoperated modes based on the confidence of their learned perception, leading to more reliable manipulation.
