ARTiS: An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Disassembly Applications

Abstract

Grasping and holding tools while using them presents a considerable challenge not only for robots but also for humans. Such a challenge is particularly noticeable in processes involving assembly and disassembly, where efficiency and consistency depend on performing rapidly adaptive tasks. Nonetheless, contemporary robotic grasping technologies that can securely manipulate tools during operation frequently have significant constraints. In this paper, introduce ARTiS (Adaptive Robotic Tool Gripper in Disassembly Systems), a novel gripper that combines the adaptability of soft grippers, the dexterity of anthropomorphic hands, and the robustness of rigid mechanisms with a soft palm and fingertips. This unique combination makes it possible to hold tools securely in a variety of situations through using active jamming in the palm and fin-ray adaptation in fingertips. Furthermore, high finger dexterity is achieved through the seven degrees of freedom design, which enables the fingertips to orient to any surface, both for automated solutions and collaborative tasks. A comprehensive evaluation was conducted using a range of conventional disassembly tools to assess the gripper’s compliance, durability, and functional versatility. More information, hardware instructions, and videos at https://romanmykhailyshyn.github.io/artis/ Note to Practitioners—This paper addresses the challenge of grasping and fixing tools in the hand to ensure their use during disassembly. The case study considers the use of three of the most commonly used tools (screwdriver, hammer, and drill) when disassembling individual machine components into smaller components. Many existing gripping devices can grasp hand tools and partially use them; however, they do not provide robust holding and adaptation to surfaces of different geometries. This paper proposes a design of a three-fingered gripping device that uses an effective combination of a jamming palm, rigid fingers, and a fin-ray fingertip for grasping/using hand tools. Using the proposed model, one can calculate the maximum permissible force applied to tools of different lengths. Knowing the frictional parameters between the gripper elements and the tools, one can determine which parameters to choose for the disassembly application based on experimental results. Positive results are highlighted in the grasping of tools without the loss of contact after use. Negative aspects are shown in the formation of vibrations in electric tools while using them with the gripper. Future research plans to improve the design of the gripper by modeling it, real-to-sim transfer, and developing a metal industrial prototype with robot learning implementation.