SoGraB: A Visual Method for Soft Grasping Benchmarking and Evaluation

TL;DR

This paper introduces SoGraB, a standardized evaluation protocol for soft robotic grippers that assesses grasping quality by measuring object deformation, enabling consistent benchmarking and comparison of different designs.

Contribution

The work presents a novel, validated protocol for evaluating soft robotic grippers based on object deformation, filling a gap in standardized assessment methods.

Findings

Successfully ranked different gripper designs using the protocol

Validated the protocol's effectiveness in selecting suitable soft grippers

Demonstrated the protocol's potential for benchmarking future designs

Abstract

Recent years have seen soft robotic grippers gain increasing attention due to their ability to robustly grasp soft and fragile objects. However, a commonly available standardised evaluation protocol has not yet been developed to assess the performance of varying soft robotic gripper designs. This work introduces a novel protocol, the Soft Grasping Benchmarking and Evaluation (SoGraB) method, to evaluate grasping quality, which quantifies object deformation by using the Density-Aware Chamfer Distance (DCD) between point clouds of soft objects before and after grasping. We validated our protocol in extensive experiments, which involved ranking three Fin-Ray gripper designs with a subset of the EGAD object dataset. The protocol appropriately ranked grippers based on object deformation information, validating the method's ability to select soft grippers for complex grasping tasks and benchmark them for comparison against future designs.