Visuo-tactile servoing framework

Introduction:

We present a novel hierarchical control framework that unifies our previous work on tactile-servoing with visual-servoing approaches to allow for robust manipulation and exploration of unknown objects, including – but not limited to – robust grasping, online grasp optimization, in-hand manipulation, and exploration of object surfaces. The control framework is divided into three layers: a joint-level position control layer, a tactile servoing control layer, and a high-level visual servoing control layer. While the middle layer provides “blind” surface exploration skills, maintaining desired contact patterns, the visual layer monitors and controls the actual object pose providing high-level finger-tip motion commands that are merged with the tactile-servoing control commands.

Because the high spatial resolution tactile array and tactile servoing method is used, the robot end-effector can actively perform slide, roll and twist motion in order to improve the contact quality with the unknown object only depending on the tactile feedback.

Our control method can be consider as another alternative option for vision-force shared control method and vision-force-tactile control method which heavily depend on the 3D force/torque sensor to perform end-effector fine manipulation after the contact happening.

We illustrate the efficiency of the proposed framework using a series of manipulation actions performed with two KUKA LWR arms equipped with a tactile sensor array as a “sensitive fingertip”. The two considered objects are unknown to the robot, i.e. neither shape nor friction properties are available.

Experiment:

Reference paper:

Qiang Li, Robert Haschke, Helge Ritter, "A Visuo-Tactile Control Framework for Manipulation and Exploration of Unknown Objects", IEEE Humanoids 2015