Jahanmahin R, Masoud S, Rickli J, Djuric A (2022) Human-robot interactions in manufacturing: A survey of human behavior modeling. Int J Robot Res 30(9):1157–1169ĭong H, Asadi E, Qiu C, Dai J, Chen I-M (2018) Geometric design optimization of an under-actuated tendon-driven robotic gripper. Int J Mach Tools Manuf 46(12):1350–1361ĭollar AM, Howe RD (2011) Joint coupling design of underactuated hands for unstructured environments. IEEE Robot Autom Mag 22(3):36–52Ĭhoi H, Koç M (2006) Design and feasibility tests of a flexible gripper based on inflatable rubber pockets. Front Robot AI 5Ĭalli B, Walsman A, Singh A, Srinivasa S, Abbeel P, Dollar AM (2015) Benchmarking in manipulation research: Using the yale-CMU-berkeley object and model set. Int J Adv Manuf Technol 122(2):1069– 1081īarasuol V, Villarreal-Magaña OA, Sangiah D, Frigerio M, Baker M, Morgan R, Medrano-Cerda GA, Caldwell DG, Semini C (2018) Highly-integrated hydraulic smart actuators and smart manifolds for high-bandwidth force control. Results indicate that it can grasp different objects, reaching a maximum force of 76 N per finger and a positioning accuracy in the millimetres range.Īlmasarwah N, Abdelall E, Suer GA, Pagan J, You Y (2022) Collaborative robots’ assembly system in the manufacturing area, assembly system 4.0. Experimental tests were conducted with objects from the YCB dataset featuring different sizes, weights and shapes. The gripper components are integrated into a common network for monitoring and control.

Objects to grasp are recognized using an embedded camera with integrated computer vision processing. The gripper structure is 3D-printed and includes three different types of fingers: (1) hard fingers, (2) flexible fingers, and (3) soft fingers. The power transmission was conceived to maximize the grasping force while keeping the gripper compactness.

It is a parallel gripper with a two-finger two-motor configuration. In this paper, we present the design and fabrication of a modular and low-cost 3D-printable robotic gripper to grasp and hold different objects. Traditional robot grippers are targeted to perform specific tasks, with unchangeable configurations and limited ability to adapt to different working scenarios. While there are many robot models available in the market, the number of grippers with sensing capabilities at an affordable cost is reduced. Robotic systems are key in industry 4.0 context.

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