Viko: An Adaptive Gecko Gripper with Vision-based Tactile Sensor
This work addresses the lack of tactile sensing in gecko grippers, enabling better robotic grasping for applications like object manipulation, though it is incremental as it builds on existing gecko adhesive and vision-based sensor technologies.
The researchers tackled the problem of monitoring contact state in gecko-inspired adhesive grippers by developing Viko, an adaptive gripper with a vision-based tactile sensor that achieved a maximum payload of 8N at a low fingertip pitch angle of 30 degrees.
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.