ARTiS:

An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Disassembly Applications

Roman Mykhailyshyn1,2, Yukiyasu Domae2 Kensuke Harada1,2
1Department of Systems Innovation, The University of Osaka, Osaka 560-8531, Japan
2Embodied AI Research Team, National Institute of Advanced Industrial Science and Technology (AIST), Koto City, Tokyo 135-0064, Japan
Under Review
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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 repetitive tasks. Nonetheless, contemporary robotic grasping technologies that can securely manipulate tools during operation frequently have significant constraints. In this paper, we 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. 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 due to the seven degrees of freedom design, which provides the capability to orient the fingertips to any surface, both for automated solutions and for collaborative tasks. We conducted a comprehensive evaluation using a range of conventional disassembly tools to assess gripper's compliance, durability, and functional versatility.

Performance Evaluation

ARTiS has the ability to withstand contacts and collisions, perform precise pinch grasps as well as compliant grasps, to be robust to noises in poses of objects and finally, to perform a wide variety of tasks!

Robustness to Collisions

Grasping Versatility

Task Versatility

Tools Used in Assembly and Disassembly

Real World Reinforcement Learning

Experimental evaluation for ARTiS supporting real-world reinforcement learning. The hand is used to learn to pick up a cube from trial and error. The gripper collides with the surface a total of 49 times without any damage eventually achieving a 100% success rate at the task. The video shows an example of collision and an example of a successful grasp. This experiment shows that BaRiFlex can withstand collisions that are typical in a real-world reinforcement learning training.

RL Test

RL Test Result

RL_Result

Design Concept

(a) The rigid 4-bar linkage mechanism transmits the torques from the direct drive actuator and the collision forces back to it, enabling (b) smooth back-drive motion, and facilitating (c) parallel precise grasping when combined with the underactuated fingertips. The torsional springs at the fingertips further enhance robustness by absorbing collision forces. The inner linkage is constructed with a Fin-Ray structure of soft 3D printed material that yields (d) compliant grasping with adaption to the objects’ shape, increasing grasp versatility. The design is simple, with only one actuated DoF and no gearbox, cost is under 500 USD, and is manufacturable in one day with two 3D printers.

CAD design for BaRiFlex

CAD_Design

Design Specification

Design_Table

Grasping Versatility

The target objects are placed at five locations (up, down, left, right, and center with 5mm distance) and with four orientations (15, 30, 45 degrees) to evaluate the tolerance of the grippers to inaccuracies in poses. We test multiple YCB objects with different shapes, sizes, surfaces, and weights. BaRiFlex demonstrates a superior grasp versatility in all cases, especially with objects that require pinch grasps or conformity, thanks to its rigid-flexible design.

Rigid

Fin-Ray Soft

ARTiS

GV Result

GV_Result

Task Versatility

ARTiS is mounted on a portable device and used by a human to perform multiple tasks such as opening heavy door, opening fridge door, catching a fast moving object. Through this human-controlled manipulation, we empirically evidence the high task-variability enabled by BaRiFlex, which covers a significant fraction of possible tasks in household domains.

Open Door-1

Open Door-2

Open Fridge

Catch the ball

Robustness Test

An accurate linear stepper motor presses on the tested hand (Rigid, 95A Fin-Ray Soft, 87A Fin-Ray Soft, and BaRiFlex). The reactive forces corresponding to different collision distances are recorded (Right). BaRiFlex exhibits the highest compliance, being able to absorb more impact forces, which facilitates interactions and learning in unstructured environments.

Rigid

Soft 95A

Soft 87A

ARTiS

Robustness Test Result

Robustness/Compliance Result

Durability & Precision Test

The test involves the gripper’s fingertip pressing a dial indicator with a resolution of 0.001 inches, 25 times. We measure the actual displacement of the dial indicator. As can be seen in the graph (rightmost figure), the variance in the actual displacement is very low (maximum deviation is 0.0889 mm), demonstrating high precision of BaRiFlex.

Durability

Precision

Precision Result

Precsion Result

ARTiS

@misc{mykhailyshyn_artis_2025,
	title = {ARTiS: An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Assembly and Disassembly Applications},
	url = {http://arxiv.org/abs/},
	doi = {10.48550/arXiv.},
	publisher = {arXiv},
	author = {Roman, Mykhailyshyn and Domae, Yukiyasu and Kensuke, Harada},
	month = dec,
	year = {2025}}