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cs.RO2024
Positive-Unlabeled Constraint Learning for Inferring Nonlinear Continuous Constraints Functions from Expert Demonstrations
Baiyu Peng, Aude Billard
Planning for diverse real-world robotic tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to…
cs.LG2024
Learning Constraint Network from Demonstrations via Positive-Unlabeled Learning with Memory Replay
Baiyu Peng, Aude Billard
Planning for a wide range of real-world tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to…