Dexterity robotic hands can (Cummings, 1996) greatly enhance the functionality of humanoid robots, but the making of such hands with not only human-like appearance but also the capability of performing the natural movement of social robots is a challenging problem. The first challenge is to create the hand’s articulated structure and the second challenge is to actuate it to move like a human hand. A robotic hand for humanoid robot should look and behave human like. At the same time, it also needs to be light and cheap for widely used purposes. We start with studying the biomechanical features of a human hand and propose a simplified mechanical model of robotic hands, which can achieve the important local motions of the hand. Then, we use 3D modeling techniques to create a single interlocked hand model that integrates pin and ball joints to our hand model. Compared to other robotic hands, our design saves the time required for assembling and adjusting, which makes our robotic hand ready-to-use right after the 3D printing is completed. Finally, the actuation of the hand is realized by cables and motors. Based on this approach, we have designed a cost-effective, 3D printable, compact, and lightweight robotic hand. Our robotic hand weighs 150 g, has 15 joints, which are similar to a real human hand, and 6 Degree of Freedom (DOFs). It is actuated by only six small size actuators. The wrist connecting part is also integrated into the hand model and could be customized for different robots such as Nadine robot (Magnenat Thalmann et al., 2017). The compact servo bed can be hidden inside the Nadine robot’s sleeve and the whole robotic hand platform will not cause extra load to her arm as the total weight (150 g robotic hand and 162 g artificial skin) is almost the same as her previous unarticulated robotic hand which is 348 g. The paper also shows our test results with and without silicon artificial hand skin, and on Nadine robot.

In the field of robotic hand design, soft body and anthropomorphic design are two trends with a promising future. Designing soft body anthropomorphic robotic hands with human-like grasping ability, but with a simple and reliable structure, is a challenge that still has not been not fully solved. In this paper, we present an anatomically correct robotic hand 3D model that aims to realize the human hand’s functionality using a single type of 3D-printable material. Our robotic hand 3D model is combined with bones, ligaments, tendons, pulley systems, and tissue. We also describe the fabrication method to rapidly produce our robotic hand in 3D printing, wherein all parts are made by elastic 50 A (shore durometer) resin. In the experimental section, we show that our robotic hand has a similar motion range to a human hand with substantial grasping strength and compare it with the latest other designs of anthropomorphic robotic hands. Our new design greatly reduces the fabrication cost and assembly time. Compared with other robotic hand designs, we think our robotic hand may induce a new approach to the design and production of robotic hands as well as other related mechanical structures.

Most current anthropomorphicrobotic hands can realize part of the human hand functions, particularly for object grasping. However, due to the complexity of the human hand, few current designs target at daily object manipulations, even for simple actions like rotating a pen. To tackle this problem, we introduce a gesture based framework, which adopts the widely-used 33 grasping gestures of Feix as the bases for hand design and implementation of manipulation. In the proposed framework, we first measure the motion ranges of human fingers for each gesture, and based on the results, we propose a simple yet dexterous robotic hand design with 13 degrees of actuation. Furthermore, we adopt a frame interpolation based method, in which we consider the base gestures as the key frames to represent a manipulation task, and use the simple linear interpolation strategy to accomplish the manipulation. To demonstrate the effectiveness of our framework, we define a three-level benchmark, which includes not only 62 test gestures from previous research, but also multiple complex and continuous actions. Experimental results on this benchmark validate the dexterity of the proposed design and our video is available in https://drive.google.com/file/d/1wPtkd2P0zolYSBW7_3tVMUHrZEeXLXgD/view?usp=sharing.

When building robotic hands, researchers are always face with two main issues of how to make robotic hands look human-like and how to make robotic hands function like real hands. Most existing solutions solve these issues by manually modelling the robotic hand [10-18]. However, the design processes are long, and it is difficult to duplicate the geometry shape of a human hand. To solve these two issues, this paper presents a simple and effective method that combines 3D printing and digitization techniques to create a 3D printable cable-driven robotic hand from scanning a physical hand. The method involves segmenting the 3D scanned hand model, adding joints, and converting it into a 3D printable model. Comparing to other robotic solutions, our solution retains more than 90% geometry information of a human hand1, which is attained from 3D scanning. Our modelling progress takes around 15 minutes that include 10 minutes of 3D scanning and five minutes for changing the scanned model to an articulated model by running our algorithm. Compared to other articulated modelling solutions [19, 20], our solution is compatible with an actuation system which provides our robotic hand with the ability to mimic different gestures. We have also developed a way of representing hand skeletons based on the hand anthropometric. As a proof of concept, we demonstrate our robotic hand's performance in the grasping experiments.