I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation

Policies trained offline from teleoperated demonstrations can degrade outside their training distribution. This gap is particularly acute in long-horizon whole-body mobile manipulation, where long horizons amplify compounding errors and coordinated arm, torso, and base motion makes exhaustive demonstration coverage impractical.

摘自论文摘要，摘要生成中。