Toward Following Changes in a Human's Posture: Stroking Motion Generation Using a Mobile Manipulator and an RGB-D Camera

While the conventional stroking motions using robot arms in physical human-robot interaction were planned from the pre-recognized shape of the target, it’s not practical because the movements of the target body during stroking are not considered. In this paper, we propose a stroking motion generation method using a mobile manipulator and an RGB- D camera to follow changes in the target human’s posture. Specifically, we first extract the target subject with image recognition and segmentation, and point cloud processing. Next, we generate the target part’s 3D model and a motion trajectory on the model. Finally, we repeatedly update the trajectory by following changes in the target part’s posture using an Iterative Closest Point (ICP) algorithm. For evaluation, the proposed method was implemented on a mobile manipulator HSR. Then, stroking motions were generated on a human-shaped robot’s back with various movements, and the alignment success score and the alignment error were measured. From the results, we confirmed that the motion generation was highly successful and occlusion by the manipulator’s arm affected the alignment.