Robot-Grabber Cooperative Localization under Highly Dynamic Clearing Operation of Bulk Carriers

Abstract

The unloading of bulk carriers is often accompanied by high dynamic changes in the cargo hold, which in turn brings difficulties in perception and localization within the hold for the clearing operation. To address the high risk and low efficiency of manual observations, this paper introduces a robot-grabber collaborative localization method for highly dynamic clearing scenarios of bulk carriers. Firstly, a collaborative localization system is constructed to enable unobstructed perception and autonomous localization of the cargo hold clearing robot and the grabber. The point cloud intensity and distance constraints are utilized to accurately determine the calibration parameters in this system, achieving unified localization of these collaborative equipment. Additionally, a multi-objective factor graph optimization based cooperative localization method is proposed to address the dynamic interference of bulk material and grabber in the cargo hold, taking into account the multi-end observation of the robot perception and system calibration, thereby obtaining robust and high-precision collaborative localization results. Finally, experiments are conducted in real port scenarios of bulk carrier clearing to validate the effectiveness of the proposed algorithm.