Imitation Learning (IL), also referred to as Learning from Demonstration (LfD), holds
significant promise for capturing expert motor skills through efficient imitation, facilitating …

This paper provides a structured and practical roadmap for practitioners to integrate learning
from demonstration (LfD) into manufacturing tasks, with a specific focus on industrial …

Compliance plays a crucial role in manipulation, as it balances between the concurrent
control of position and force under uncertainties. Yet compliance is often overlooked by …

Reinforcement learning (RL) is a popular technique that allows an agent to learn by trial and
error while interacting with a dynamic environment. The traditional Reinforcement Learning …

Reinforcement learning (RL) has emerged as a promising paradigm in complex and
continuous robotic tasks, however, safe exploration has been one of the main challenges …

Robotic tasks which involve uncertainty–due to variation in goal, environment configuration,
or confidence in task model–may require human input to instruct or adapt the robot. In tasks …

Percutaneous puncture is a widely used procedure in the diagnosis and therapy of cancer
such as biopsy and ablation operations, while the organs in the thoracic and abdominal …

Acquiring human skills offers an efficient approach to tackle complex task planning
challenges. When performing a learned skill model for a continuous contact task, such as …

Robot assembly skill learning has gradually become a research focus in the field of
industrial robots. To improve the learning efficiency and adaptability of robot peg-in-hole …

Contact-rich manipulation involves kinematic constraints on the task motion, typically with
discrete transitions between these constraints during the task. Allowing the robot to detect …