Frictional and Prismatic Pin-Array Gripper for Universal Gripping and Stable Tool Manipulation

Global trend in robotics has shifted toward deploying humanoid robots and mobile manipulators in industrial settings to automate repetitive and structured tasks traditionally performed by human workers. However, most tools and equipment are de- signed for human hands, and current grippers or end-effectors are highly specialized, limiting their ability to fully replace human handling of simple tools and tasks. This study proposes a novel frictional and prismatic pin-array gripper developed for universal gripping and tool manipulation. A pin-array structure of the grip- per mimics the behavior of soft grippers while incorporating rigid components, enabling adaptability to various shapes and sizes. Each pin features semiautomatic actuation through a compression spring, supporting the underactuated mechanism. Most existing studies on grippers focus on simple pick-and-place tasks, whereas the proposed gripper extends functionality to practical tool usage. Enabled by the pin-array structure, it provides increased contact surface and support points, ensuring stable gripping and enhanced manipulation performance. In the evaluation, the pin-array grip- per achieved a payload capacity of 2400 g, significantly outper- forming the conventional RG2-FT gripper and the frictional flat gripper, which reached maximum capacities of 800 and 400 g, respectively. It also exhibited higher grasping forces, measuring 1.17 times greater than the RG2-FT gripper and up to 23 times greater than the frictional flat gripper. For tool manipulation, the pin-array gripper exhibited significantly lower manipulation errors, with 21.67 and 6.59 times fewer errors than the RG2-FT and flat grippers, respectively, when handling the hammer, and Received 6 May 2025; revised 28 September 2025; accepted 11 October 2025. Date of publication 28 October 2025; date of current version 1 December 2025. This work was supported in part by the Ministry of Trade, Industry & Energy (MOTIE, Korea) through the Industrial Technology Innovation Program under Grant RS-2024-00507783, “The development of AI-based predictive mainte- nance and mobile autonomous robots for high-risk tasks in steel manufacturing processes” and in part by the National Research Foundation of Korea (NRF), through the Korea government, MSIT under Grant RS-2024-00356951. This article was recommended for publication by Associate Editor C. Della Santina and Editor M. Yim upon evaluation of the reviewers’ comments. (Cheonghwa Lee and Hyeongwon Kim contributed equally to this work.) (Corresponding author: Sung-Hoon Ahn.) Cheonghwa Lee is with the Department of the Electrical and Computer Engineering,SeoulNationalUniversity,Seoul08826,SouthKorea,andalsowith the School of Mechanical Engineering, Kumoh National Institute of Technology, Gumi 39177, South Korea (e-mail: haya.c.lee@kumoh.ac.kr). Hyeongwon Kim and Midum Oh are with the Department of Mechanical Engineering, Seoul National University, Seoul 08826, South Korea (e-mail: alstk1956@snu.ac.kr; midumoh@snu.ac.kr). Kisu Ok is with the Department of Electrical and Computer Engi- neering, Seoul National University, Seoul 08826, South Korea (e-mail: ksokngu@snu.ac.kr). Sung-Hoon Ahn is with the Department of Mechanical Engineering, Seoul National University, Seoul 08826, South Korea, and also with the Institute of Advanced Machines and Design, Seoul National University, Seoul 08826, South Korea (e-mail: ahnsh@snu.ac.kr). This article has supplementary downloadable material available at https://doi.org/10.1109/TRO.2025.3626656, provided by the authors. Digital Object Identifier 10.1109/TRO.2025.3626656 7.69 and 4.45 times fewer for the metal file. In addition, qualitative demonstrations in universal gripping, omnidirectional gripping, and tool usage further validated the gripper’s performance in mobile manipulator tasks.