Soft robots with good sense

Monday, 29 June, 2020

Soft robots have potential in the food industry but have been limited due to their lack of good sensing. Now researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed new tools to let a soft robot feel what it is touching (tactile sensing) and sense the positions of its fingers (proprioception).

“Soft robot hands have sensorised skins that allow them to pick up a range of objects, from delicate, such as potato chips, to heavy, such as milk bottles,” said CSAIL Director Daniela Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science and the deputy dean of research for the MIT Stephen A. Schwarzman College of Computing.

The researchers reported in two papers: One paper builds off last year’s research from MIT and Harvard University, where a team developed a soft and strong robotic gripper in the form of a cone-shaped origami structure. It collapses in on objects much like a Venus flytrap, to pick up items that are as much as 100 times its weight.

To get that newfound versatility and adaptability even closer to that of a human hand, the team came up with a sensible addition: tactile sensors, made from latex ‘bladders’ (balloons) connected to pressure transducers. The new sensors let the gripper not only pick up objects as delicate as potato chips, but it also classifies them — letting the robot better understand what it’s picking up, while also exhibiting that light touch.

When classifying objects, the sensors correctly identified 10 objects with over 90% accuracy, even when an object slipped out of grip.

“Unlike many other soft tactile sensors, ours can be rapidly fabricated, retrofitted into grippers, and show sensitivity and reliability,” said MIT postdoc Josie Hughes, the lead author on a new paper about the sensors. “We hope they provide a new method of soft sensing that can be applied to a wide range of different applications in manufacturing settings, like packing and lifting.”

In a second paper, a group of researchers created a soft robotic finger called GelFlex that uses embedded cameras and deep learning to enable high-resolution tactile sensing and “proprioception” (awareness of positions and movements of the body).

The gripper, which looks much like a two-finger cup gripper you might see at a vending machine, uses a tendon-driven mechanism to actuate the fingers. When tested on metal objects of various shapes, the system had over 96% recognition accuracy.

“Our soft finger can provide high accuracy on proprioception and accurately predict grasped objects, and also withstand considerable impact without harming the interacted environment and itself,” said Yu She, lead author on the GelFlex paper. “By constraining soft fingers with a flexible exoskeleton, and performing high-resolution sensing with embedded cameras, we open up a large range of capabilities for soft manipulators.”