Structural Interlocking-Based Weaving Gripper for Enhanced Grasping Performance
Yuvin Jun, Daehyun Kim, Seokhwan Jeong, Joonbum Bae, Kahye Song
AI summary
Problem
Soft robotic grippers face a fundamental trade-off between compliance and load-bearing capacity, while rigid grippers lack the adaptability needed for unstructured environments.
Approach
The authors designed a gripper using closed-loop wires that interlock through relative rotation, paired with a geometric prediction model to systematically control grasping configurations and aperture.
Key results
- Achieves up to 170.19 kg·f payload capacity with actuation torque under 0.02 N·m
- Prediction model quantifies wire interlocking and aperture variation for systematic design
- Enables stable grasping of diverse, irregular, and fragile objects through passive compliance
- Successfully integrated with a continuum robot to retrieve objects from confined, curved tunnels
Why it matters
This approach resolves the flexibility-strength trade-off in soft grippers, providing a scalable, low-torque solution for manipulation in unstructured and confined environments.
Abstract
Robotic grippers have been extensively developed to enable stable and efficient object manipulation across diverse applications. While soft grippers offer high adaptability and safety, their performance remains constrained by an inherent trade-off between flexibility and load-bearing capacity. This study was undertaken with the objective of addressing these challenges by proposing a compact weaving gripper that exploits structurally induced interlocking. Additionally, a prediction model is developed to predict and control grasping configurations. The proposed gripper is integrated with continuum robot, enabling operation in confined environments, and demonstrates applicability across diverse robotic platforms.