In recent years, the development of robotics and artificial intelligence (AI) systems has been
nothing short of remarkable. As these systems continue to evolve, they are being utilized in …

Interactive Imitation Learning in Robotics: A Survey Page 1 Interactive Imitation Learning in
Robotics: A Survey Page 2 Other titles in Foundations and Trends® in Robotics A Survey on …

Imitation learning from human demonstrations can teach robots complex manipulation skills,
but is time-consuming and labor intensive. In contrast, Task and Motion Planning (TAMP) …

Imitation learning from a large set of human demonstrations has proved to be an effective
paradigm for building capable robot agents. However, the demonstrations can be extremely …

Imitation learning (IL) aims to extract knowledge from human experts' demonstrations or
artificially created agents to replicate their behaviors. It promotes interdisciplinary …

Effective robot learning often requires online human feedback and interventions that can
cost significant human time, giving rise to the central challenge in interactive imitation …

Commercial and industrial deployments of robot fleets at Amazon, Nimble, Plus One,
Waymo, and Zoox query remote human teleoperators when robots are at risk or unable to …

Imitation learning is a powerful tool for training robot manipulation policies, allowing them to
learn from expert demonstrations without manual programming or trial-and-error. However …

Language provides a way to break down complex concepts into digestible pieces. Recent
works in robot imitation learning use language-conditioned policies that predict actions …

Imitation learning has been applied to a range of robotic tasks, but can struggle when robots
encounter edge cases that are not represented in the training data (ie, distribution shift) …