A study on picking objects in cluttered environments: Exploiting depth features for a custom low-cost universal jamming gripper. (June 2020)

• Record Type: Journal Article
• Authors: D'Avella, Salvatore; Tripicchio, Paolo; Avizzano, Carlo Alberto
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 63(2020)
• Publication Date: 2020-06
• Subjects: Autonomous picking -- Universal jamming gripper -- Computer vision -- Collaborative robotics -- ROS; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2019.101888
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: This work aims to study a possible way to overcome current limitations on the existing robotic solutions for picking objects in cluttered environments. The system integrates a traditional parallel-jaw gripper and a custom-designed universal jamming gripper (UJG) on the Baxter bimanual collaborative robot. 3D perception technologies are employed to select suitable geometries that exploit at best the advantages of the UJG in picking objects of different shapes. Grasping tests to assess the capabilities of the custom gripper have been conducted on general objects, thus not limiting the analysis to a single manufacturing scenario. The system is shown to have a competitive success rate and to determine a suitable grasping target faster than state-of-the-art solutions. Abstract: Robotics solutions in the industrial sector are moving towards higher degrees of flexibility. In such a context, the latest research is focused on grasping technologies for material handling. The aim of this work is to study a possible way to overcome current limitations on the existing robotic solutions for picking objects in cluttered environments. Pick and place task is of fundamental relevance in automated manufacturing companies. Many industrial processes, have bin-picking as the preliminary phase task. The challenge is to handle mixed bins that contain multiple different types of parts with complex configuration to grasp in a more flexible way. Using intelligent autonomous robots for picking different kinds of objects allows industries to handle a wide assortment of parts without the need for any change in the hardware structure and design. In this manuscript, a collaborative robotics system is presented. It integrates a classical two-finger gripper and a custom designed soft-robotics end-effector in a commercial robot. In this work, 3D perception technologies are employed in order to select suitable geometries that exploit at best the advantages of the universal jamming gripper (UJG) in picking objects of different shapes. A custom algorithm that selects a suitable picking point, solving the perceptual issues posed by cluttered environments, is introduced. Grasping tests to assess the capabilities of the custom gripper have been conducted. The objects selected to test the performance of the proposed system do not consider just a specific manufacturing scenario but are meant to be more general, not limiting the analysis to a single case. Furthermore, a comparative study of the algorithmic performance of the proposed method with respect to state-of-the-art techniques is presented. The proposed system is shown to be able to grasp novel objects in a cluttered environment with a competitive success rate, determining a suitable grasping target in short time.