Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation

Chapter 4: Capacitive material detection with machine learning for robotic grasping applications

Hannes Kisner; Yitao Ding; Ulrike Thomas    Lab of Robotics and Human Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany

Abstract

Objects that are made of different materials are difficult to distinguish by vision and sensing alone when they are similarly shaped and colored. This is especially important in robotic grasping scenarios, where the grasping task can benefit from incorporating material properties and the ability of their detection in a contactless and, therefore, nondestructive way. The robot can adapt its grasping behavior according to the perceived specific material surfaces. We have demonstrated the use of machine ...