Proximity-based non-contact perception and omnidirectional point-cloud generation based on hierarchical information on fingertip proximity sensors

Abstract

In this study, we examine robotic proximity perception for both reactive control and 3D point-cloud acquisition using a multi-fingered robot hand. A reactive controller adjusts the relative position and orientation between the fingertips and the target object, while the robot-hand system gathers point-cloud data related to the shape of the object. An experimental result showed that the accuracy of the point-cloud generated using proximity perception was equivalent to or better than that of the point-cloud generated using a vision sensor. Based on the results, we propose proximity-based point-cloud acquisition using ‘non-contact perception’ motion to search the object's surface while preventing unintended collisions. The motion is then combined with the approaching and twisting motions of the robot hand. This enables multi-angles object detection complementarily with reactive fingertip control. Our experiments reveal that the proposed method can generate data-rich point-clouds for various general objects.