TY - GEN
T1 - Wireless Capacitive Tactile Sensor Arrays for Sensitive/Delicate Robot Grasping
AU - Ergun, Serkan
AU - Mitterer, Tobias
AU - Khan, Sherjeel
AU - Anandan, Narendiran
AU - Mishra, Rishabh B.
AU - Kosel, Jurgen
AU - Zangl, Hubert
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Uncertainties in grasp prediction for unknown, arbitrarily shaped objects in cluttered environments and un- certainty of the kinematics (e.g., series elastic robots or soft robots) can lead to poor grasps. For delicate objects, such poor grasps may damage the objects when they are dropped or when high local pressure is introduced in the grasping process. We propose a tactile sensor concept that allows predicting the quality of a grasp such that the object can be safely moved without being dropped. This prediction is done using an initial low force grasp and the force is only increased when the contact area is sufficiently large. The proposed customizable wireless Capacitive Tactile Sensor Array (CTSA) uses the deformation of a polymer to assess the contact area and the force distribution. A common homogeneous deformable electrode is embedded in the polymer. This electrode does not require any patterning nor any electrical connection but to ground. We present the manufacturing process which allows for robust yet cost effective realizations with a variety of electrode materials including conductive inks, conductive textiles, metal meshes and metal sheets. With the different approaches, parameters such as sensitivity and recovery time can be adjusted. Furthermore, the robustness of the sensor towards strong forces and objects with sharp edges and corners is shown. Finally, we demonstrate the benefits of the proposed sensor for grasping in a series of scenarios with rigid and soft 3D printed objects of various shapes. Allowing a reasonable false positive rate, 100 % of unsuccessful grasps in our evaluation experiments could be detected from the initial low force grasp.
AB - Uncertainties in grasp prediction for unknown, arbitrarily shaped objects in cluttered environments and un- certainty of the kinematics (e.g., series elastic robots or soft robots) can lead to poor grasps. For delicate objects, such poor grasps may damage the objects when they are dropped or when high local pressure is introduced in the grasping process. We propose a tactile sensor concept that allows predicting the quality of a grasp such that the object can be safely moved without being dropped. This prediction is done using an initial low force grasp and the force is only increased when the contact area is sufficiently large. The proposed customizable wireless Capacitive Tactile Sensor Array (CTSA) uses the deformation of a polymer to assess the contact area and the force distribution. A common homogeneous deformable electrode is embedded in the polymer. This electrode does not require any patterning nor any electrical connection but to ground. We present the manufacturing process which allows for robust yet cost effective realizations with a variety of electrode materials including conductive inks, conductive textiles, metal meshes and metal sheets. With the different approaches, parameters such as sensitivity and recovery time can be adjusted. Furthermore, the robustness of the sensor towards strong forces and objects with sharp edges and corners is shown. Finally, we demonstrate the benefits of the proposed sensor for grasping in a series of scenarios with rigid and soft 3D printed objects of various shapes. Allowing a reasonable false positive rate, 100 % of unsuccessful grasps in our evaluation experiments could be detected from the initial low force grasp.
UR - http://www.scopus.com/inward/record.url?scp=85182523661&partnerID=8YFLogxK
U2 - 10.1109/IROS55552.2023.10342163
DO - 10.1109/IROS55552.2023.10342163
M3 - Conference contribution
AN - SCOPUS:85182523661
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 10777
EP - 10784
BT - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
Y2 - 1 October 2023 through 5 October 2023
ER -