Robotic learning techniques, including supervised learning, reinforcement learning, imitation learning, and active learning, can be effectively applied to address the challenges of adaptive informative path planning (AIPP) in robotics, enabling more flexible, adaptive, and scalable solutions.
Autonomous Iterative Motion Learning (AI-MOLE) enables robotic systems with unknown, nonlinear dynamics to rapidly learn to track reference trajectories without requiring any a priori model information or manual parameter tuning.