This workshop addresses the critical problem of category-level object pose estimation and its applications within complex robotic manipulation scenarios. Pose estimation, a fundamental challenge in both 3D computer vision and robotics perception, involves accurately determining an object's complete 6-degree-of-freedom (6DoF) pose, comprising its 3D rotation and translation. Our workshop specifically focuses on advancing category-level pose estimation methods under realistic and demanding robotic manipulation settings, particularly emphasizing articulated objects, dynamic environments with potential human-object interactions, and objects subject to severe occlusions and partial visibility.