Monitoring the state of contact is essential for robotic devices, especially grippers that implement gecko-inspired adhesives where intimate contact is crucial for a firm attachment. However, due to the lack of deformable sensors, few have demonstrated tactile sensing for gecko grippers. We present Viko, an adaptive gecko gripper that utilizes vision-based tactile sensors to monitor contact state. The sensor provides high-resolution real-time measurements of contact area and shear force. Moreover, the sensor is adaptive, low-cost, and compact. We integrated gecko-inspired adhesives into the sensor surface without impeding its adaptiveness and performance. Using a robotic arm, we evaluate the performance of the gripper by a series of grasping test. The gripper has a maximum payload of 8N even at a low fingertip pitch angle of 30 degrees. We also showcase the gripper's ability to adjust fingertip pose for better contact using sensor feedback. Further, everyday object picking is presented as a demonstration of the gripper's adaptiveness.
@article{arxiv.2105.00680,
title = {Viko: An Adaptive Gecko Gripper with Vision-based Tactile Sensor},
author = {Chohei Pang and Kinwing Mak and Yazhan Zhang and Yang Yang and Yu Alexander Tse and Michael Yu Wang},
journal= {arXiv preprint arXiv:2105.00680},
year = {2021}
}
Comments
This paper is accepted to ICRA2021, please contact corresponding author Y. Tse (yatse@connect.ust.hk) for details