Real-Time Grasp Quality in Boundary-Constrained Granular Swarm Robots
Declan Mulroy, David Cañones Bonham, Matthew Spenko, Ankit Srivastava
Abstract
Soft robotic grippers offer advantages over rigid end effectors but are typically coupled to a rigid robot for locomotion. In contrast, this paper details a soft robot for both locomotion and grasping. The system is a type of boundaryconstrained granular swarm robot, which is composed of a closed-loop series of active (capable of locomotion) sub-robots. Prior work has shown how this type of robot is capable of locomotion and grasping. For this paper, we propose a new grasping strategy and demonstrate real-time grasp quality evaluation using pressure sensors and the Ferrari-Canny grasp metric. The grasping strategy leverages gradient-based control via distance functions and dynamic system planning to achieve desired robot geometries for effective grasping. Previous research primarily used pull tests to evaluate grasping efficacy, which lacked realtime feedback on grasp quality. Simulated and experimental results confirm the effectiveness of this method.
BibTeX
@inproceedings{icra2025_realtimegraspqua,
title = {Real-Time Grasp Quality in Boundary-Constrained Granular Swarm Robots},
author = {Declan Mulroy and David Cañones Bonham and Matthew Spenko and Ankit Srivastava},
booktitle = {ICRA 2025},
year = {2025}
}