Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation

Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang, Jacinto E. Colan Zaita, Tadayoshi Aoyama, Yasuhisa Hasegawa, Boris Belousov, Kay Hansel, Jan Peters

Abstract: Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic information during in-hand manipulation. This nature of tactile sensors makes them a perfect match for haptic feedback applications. In this paper, we propose a contact force estimation method using the vision-based tactile sensor DIGIT [1], and apply it to a position-force teleoperation architecture for force feedback. The force estimation is carried out by (1) building a depth map for DIGIT gel’s surface deformation measurement, and (2) applying a regression algorithm on estimated depth data and ground truth force data to get the depth-force relationship. The experiment is performed by constructing a grasping force feedback system with a haptic device as a leader robot and a parallel robot gripper as a follower robot, where the DIGIT sensor is attached to the tip of the robot gripper to estimate the contact force. The preliminary results show the capability of using the low-cost vision-based sensor for force feedback applications.