Work

Proposal of a Grasp Verification Method Utilizing Background Subtraction and Depth Information

Year: 2025

Type: conference-paper

Abstract: Commonly grasp verification approach involves using the opening width of the robot's gripper.However, methods based on the opening width of the gripper may not apply to slender objects.In this study, we propose a grasp verification method using background subtraction.Our proposed method uses depth information to mask the background, isolating only the images of the gripper and the grasped object.Subsequently, a difference image is created by comparing the current image with the pre-grasp state, and the grasp state is detected based on the magnitude of the observed changes.The method minimizes environmental influences by masking the background, enabling highly accurate grasp verification even for complex objects.Through experiments, we validate the effectiveness of the proposed method.

Source: Proceedings of International Conference on Artificial Life and Robotics

DOI: 10.5954/icarob.2025.os17-6

Authors: Ryo Terashima, Yuga Yano, Koshun Arimura, Hakaru Tamukoh

Institution: Kyushu Institute of Technology

Language: English

Topic: Robot Manipulation and Learning

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

Funders: Japan Society for the Promotion of Science, Advanced Low Carbon Technology Research and Development Program

Awards: Realization and Fundamental Elucidation of Intelligent Processing Using Material Reservoirs with Extremely High Information Density, G2364066242, G7712781798