Efficient Grasping of Oscillating Apples using Task Parameterized Learning from Demonstration

A new method called DualLQR is proposed to efficiently grasp oscillating apples using task parameterized learning from demonstration. DualLQR uses a dual linear quadratic regulator (LQR) setup to track the oscillating target during the final approach while minimizing the overall path length.