ICRA 2024poster0 citations

Embedded air channels transform soft lattices into sensorized grippers

Annan Zhang, Lillian Chin, Daniel L. Tong, Daniela Rus

Abstract

Sensing plays a pivotal role in robotic manipulation, dictating the accuracy and versatility with which objects are handled. Vision-based sensing methods often suffer from fabrication complexity and low durability, while approaches that rely on direct measurements on the gripper often have limited resolution and are difficult to scale. Here, we present a soft robotic gripper made out of two cubic lattices that are sensorized by embedding air channels within the structure. The lattices are 3D printed from a single build material, simplifying the fabrication process. The flexibility of this approach offers significant control over sensor and lattice design, while the pressure-based internal sensing provides measurements with minimal disruption to the grasping surface. With only 12 sensors, 6 per lattice, this gripper can estimate an object’s weight and location and offer new insights into grasp parameters like friction coefficients and grasp force.

BibTeX
@inproceedings{icra2024_embeddedairchann,
  title = {Embedded air channels transform soft lattices into sensorized grippers},
  author = {Annan Zhang and Lillian Chin and Daniel L. Tong and Daniela Rus},
  booktitle = {ICRA 2024},
  year = {2024}
}
Embedded air channels transform soft lattices into sensorized grippers · ICRA 2024