Abstract: This paper proposes a hybrid kinematic calibration framework for serial robotic manipulators that integrates analytical parameter identification with data-driven residual learning. First, ...
Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.