Michigan State finds that stronger soft gripper could lead to safer human-robot interactions

The Robot Report
Michigan State finds that stronger soft gripper could lead to safer human-robot interactions

The hybrid flexible gripper can generate larger grasping force than a traditional pure soft hand and is more stable for accurate manipulation, said Michigan State professor Changyong Cao.

Rigid end effectors for industrial robots offer speed, strength, and precision, while compliant or soft grippers offer variability and safer human-machine interactions. A team of Michigan State University engineers has designed and developed a novel humanoid hand that may be able to bridge the gap.

“The novel humanoid hand design is a soft-hard hybrid flexible gripper. It can generate larger grasping force than a traditional pure soft hand, and simultaneously be more stable for accurate manipulation than other counterparts used for heavier objects,” said lead author Changyong Cao, director of the Laboratory for Soft Machines and Electronics at Michigan State and assistant professor in Packaging, Mechanical Engineering, and Electrical and Computer Engineering.

This new research, “Soft Humanoid Hands with Large Grasping Force Enabled by Flexible Hybrid Pneumatic Actuators,” is published in Soft Robotics.

Michigan State overcomes soft gripper limitations

Generally, soft-hand grippers — which are used primarily in settings where an object may be fragile, light and irregularly shaped — present several disadvantages: sharp surfaces, poor stability in grasping unbalanced loads, and relatively weak grasping force for handling heavy loads.

When designing the new model, Cao and his team took into consideration a number of human-environment interactions, from fruit picking to sensitive medical care. They identified that some processes require a safe but firm interaction with fragile objects; most existing gripping systems are not suitable for these purposes.

The Michigan State team explained that the design novelty resulted in a prototype demonstrating the merits of a responsive, fast, lightweight gripper capable of handling a multitude of tasks that traditionally required different types of gripping systems.

Each finger of the soft humanoid hand is constructed from a flexible hybrid pneumatic actuator — or FHPA — driven to bend by pressurized air, creating a modular framework for movement in which each digit moves independently of the others.

Hybrid robot hand adaptable to heavy loads

“Traditional rigid grippers for industrial applications are generally made of simple but reliable rigid structures that help in generating large forces, high accuracy and repeatability,” Cao explained. “The proposed soft humanoid hand has demonstrated excellent adaptability and compatibility in grasping complex-shaped and fragile objects while simultaneously maintaining a high level of stiffness for exerting strong clamping forces to lift heavy loads.”

Michigan State Cao

Changyong Cao, director of the Laboratory for Soft Machines and Electronics at MSU and assistant professor in Packaging, Mechanical Engineering, and Electrical and Computer Engineering. Source: MSU

In essence, the best of both worlds, he said. The FHPA is composed of both hard and soft components, built around a unique structural combination of actuated air bladders and a bone-like spring core.

“They combine the advantages of the deformability, adaptability and compliance of soft grippers while maintaining the large output force originated from the rigidity of the actuator,” Cao said.

Possible applications and future research

Cao said the prototype could be useful in industries such as fruit picking, automated packaging, medical care, rehabilitation, and surgical robotics.

With ample room for future research and development, the team hopes to combine its advances with Cao’s recent work on so-called smart grippers, integrating printed sensors in the gripping material. And by combining the hybrid gripper with soft arms, the researchers aim to more accurately mimic precise human actions.

The co-authors of the paper include Xiaomin Liu, MSU student Shoue Chen, MSU Foundation Prof. Xiaobo Tan from the Department of Electrical and Computer Engineering, and Yunwei Zhao and Dexu Geng from Beihua University.

This research was partially funded by the U.S. Department of Agriculture-National Institute of Food and Agriculture (1016788), MSU Strategic Partnership Grant, National Natural Science Foundation of China (51275004) and an MSU Startup Grant.

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