Lasso Gripper: A String Shooting-Retracting Mechanism for Shape-Adaptive Grasping

TL;DR

This paper introduces the Lasso Gripper, a novel shape-adaptive robotic gripper that uses a string launching and retraction mechanism inspired by traditional tools, enabling gentle and adjustable grasping of various objects.

Contribution

The paper presents a new string-based gripper design with a dynamic model and specialized mechanism to prevent tangling, expanding grasping capabilities beyond traditional rigid or antipodal grippers.

Findings

Successfully grasped diverse objects including fragile vegetables and figurines.

Demonstrated adjustable grasp size by controlling motor speeds.

Developed a dynamic model for string curve estimation and workspace analysis.

Abstract

Handling oversized, variable-shaped, or delicate objects in transportation, grasping tasks is extremely challenging, mainly due to the limitations of the gripper's shape and size. This paper proposes a novel gripper, Lasso Gripper. Inspired by traditional tools like the lasso and the uurga, Lasso Gripper captures objects by launching and retracting a string. Contrary to antipodal grippers, which concentrate force on a limited area, Lasso Gripper applies uniform pressure along the length of the string for a more gentle grasp. The gripper is controlled by four motors-two for launching the string inward and two for launching it outward. By adjusting motor speeds, the size of the string loop can be tuned to accommodate objects of varying sizes, eliminating the limitations imposed by the maximum gripper separation distance. To address the issue of string tangling during rapid retraction, a specialized mechanism was incorporated. Additionally, a dynamic model was developed to estimate the string's curve, providing a foundation for the kinematic analysis of the workspace. In grasping experiments, Lasso Gripper, mounted on a robotic arm, successfully captured and transported a range of objects, including bull and horse figures as well as delicate vegetables. The demonstration video is available here: https://youtu.be/PV1J76mNP9Y.