Robotic Data

Robotic data collection research focuses on efficiently gathering high-quality data for training and improving robot capabilities. Current efforts concentrate on developing adaptive path planning algorithms, often employing Gaussian processes (including non-stationary kernels like the Attentive Kernel) and reinforcement learning, to optimize data acquisition strategies in diverse environments. These advancements are crucial for improving robot autonomy and performance in various applications, from environmental monitoring to manipulation tasks, by enabling more efficient and effective data-driven learning.