Clarification on Plug Orientation Relative to Gripper Across Evaluation Trials

In a detailed forum post dated March 5, 2026, a competitor under the username Rocky_Shao sought critical clarification for the 'AI for Industry Challenge,' a robotics and AI competition. The core question revolves around the plug's starting pose relative to the robot gripper during the evaluation phase. Examining the provided sample_config.yaml file, Rocky_Shao noted specific gripper_offset coordinates (x, y, z) and orientation values (roll, pitch, yaw) that appeared consistent across sample trials, with only a slight variation in the z-component. The competitor is asking competition organizers to confirm if these orientation values are guaranteed to be fixed or if they could be randomized, which fundamentally changes the complexity of the task.

Understanding this parameter is not a minor detail; it dictates the entire architectural approach for competing AI policies. If the plug orientation is a known, static offset from the gripper's Tool Center Point (TCP), teams can simplify their solution by hard-coding this relationship, focusing computational effort solely on locating the target port. However, if the orientation is randomized, teams must develop a robust perception and localization pipeline to dynamically solve for the plug's pose in addition to the port's—a significantly more challenging problem. The answer will determine whether this is primarily a manipulation and control challenge or a full perception-planning-control integration task, directly affecting which teams have a competitive edge based on their technical stack and strategy.