AAPOE: Automated Artifacts Position and Orientation Estimation in Cultural Heritage

Pose estimation of cultural heritage artifacts is essential for the accurate alignment of 3D scans. This paper proposes a novel robotic arm-based strategy named Automated Artifacts Position and Orientation Estimation (AAPOE), which detects artifacts, re-identifies them if moved, and estimates and tracks their poses within the workspace. The robotic arm is equipped with a 3D scanner that captures depth maps from different positions, converting them into point clouds to form a complete scene. AAPOE filters out the ground plane, clusters the point cloud to detect individual artifacts, and re-identifies them if moved. The artifacts detected for the first time are processed to assign unique poses to each of them based on principal component analysis of their point clouds. When the artifacts are re-identified, AAPOE applies a rotate-until-converge approach for alignment, ultimately estimating their poses. These steps ensure accurate pose estimation and tracking, which are critical for fine-grained scanning and robot manipulation in cultural heritage applications. Experiments demonstrate that the estimated poses accurately align the artifacts placed and scanned in any random position within the workspace.