Co-Programming Shape Morphing and Interaction Forces of Soft Grippers for Compliant Grasping

Area of Science:

• Robotics
• Mechanical Engineering
• Materials Science

Background:

• Soft grippers are crucial for handling delicate objects, but current designs lack precise control over deformation and interaction forces.
• Existing designs often prioritize fingertip performance over controlled force distribution.

Purpose of the Study:

• To develop a novel topology-optimization framework for soft gripper design.
• To achieve large-area contact and uniformly distributed interaction forces for enhanced grasping.
• To enable precise regulation of gripper deformation and forces during object manipulation.

Main Methods:

• A topology-optimization framework was developed to concurrently regulate gripper shape morphing and contact force distribution.
• The grasped object was modeled using a spring system.
• A gradient-based optimization algorithm was employed to generate the soft adaptive gripper design.

Main Results:

• The optimized soft gripper design achieved uniform wrapping over a large area.
• Interaction forces were uniformly distributed and biased towards the palm side to counteract gravity.
• Quantitative experiments and grasping tests confirmed superior compliance, adaptability, and load capacity.

Conclusions:

• The proposed topology-optimization framework successfully designs soft grippers with controlled shape morphing and interaction forces.
• The optimized grippers exhibit enhanced performance in grasping a wide range of objects, from fragile to heavier items.
• This approach offers a pathway to advanced soft robotic manipulation systems.