scholarly journals Kinematic Analysis and Dimensional Synthesis of a Meso-Gripper

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Guochao Bai ◽  
Xianwen Kong ◽  
James Millar Ritchie

Abstract In recent years, applications in industrial assemblies within a size range from 0.5 mm to 100 mm are increasing due to the large demands for new products, especially those associated with digital multimedia. Research on grippers or robotic hands within the mesoscopic scale of this range has not been explored in any great detail. This paper outlines the development of a gripper to bridge the gap between microgrippers and macrogrippers by extending the gripping range to the mesoscopic scale, particularly without the need to switch grippers during industrial assembly. The mesoscopic scale gripper (meso-gripper) researched in this work has two modes of operation: passive adjusting mode and angled gripping mode, adapting its configuration to the shape of object automatically. This form of gripping and the associated mechanism are both novel in their implementation and operation. First, the concept of mesoscopic scale in robotic gripping is presented and contextualized around the background of inefficient hand switching processes and applications for assembly. The passive adjusting and angled gripping modes are then analyzed and a dual functional mechanism design proposed. A geometric constraint method is then demonstrated which facilitates task-based dimensional synthesis after which the kinematics of synthesized mechanism is investigated. The modified synthesized mechanism gripper is then investigated according to stiffness and layout. Finally, a 3D printed prototype is successfully tested, and the two integrated gripping modes for universal gripping verified.

Author(s):  
Guochao Bai ◽  
Xianwen Kong ◽  
James Millar Ritchie

In recent years, applications in industrial assemblies within a size range from 0.5mm to 100mm are increasing due to the large demands for digital multimedia products. Research on grippers or robotic hands within the mesoscopic scale of this range has not been well explored. This paper proposes a mesoscopic scale gripper (meso-gripper) which has two modes: passive adjusting mode and an angled precision gripping mode. The gripper adjusts its shape automatically according to the appropriate mode. This form of gripping and the associated mechanism are novel in their implementation and operation. The meso-gripper which has metamorphic characteristics is generated by integrating a remote center of motion (RCM) mechanism with a cross four-bar (CFB) linkage. The dimensional synthesis of the gripper is outlined for a specified task-based gripping followed by the analysis of the synthesizing mechanism. A differential mechanism is adopted to increase the flexibility of the meso-gripper. Prototype is fabricated and tested using 3D printing technology to verify the feasibility of the design.


2020 ◽  
Vol 17 (03) ◽  
pp. 2050010
Author(s):  
Saeed Saeedvand ◽  
Hadi S. Aghdasi ◽  
Jacky Baltes

Although there are several popular and capable humanoid robot designs available in the kid-size range, they lack some important characteristics: affordability, being user-friendly, using a wide-angle camera, sufficient computational resources for advanced AI algorithms, and mechanical robustness and stability are the most important ones. Recent advances in 3D printer technology enables researchers to move from model to physical implementation relatively easy. Therefore, we introduce a novel fully 3D printed open platform humanoid robot design named ARC. In this paper, we discuss the mechanical structure and software architecture. We show the capabilities of the ARC design in a series of experimental evaluations.


2019 ◽  
Vol 17 ◽  
pp. 206-215 ◽  
Author(s):  
Jiayi Li ◽  
Liangliang Li ◽  
Jin Zhou ◽  
Zhi Zhou ◽  
Xiao-ling Wu ◽  
...  

Author(s):  
Edgar Simo-Serra ◽  
Francesc Moreno-Noguer ◽  
Alba Perez-Gracia

In this paper, we explore the idea of designing non-anthropomorphic multi-fingered robotic hands for tasks that replicate the motion of the human hand. Taking as input data a finite set of rigid-body positions for the five fingertips, we develop a method to perform dimensional synthesis for a kinematic chain with a tree structure, with five branches that share three common joints. We state the forward kinematics equations of relative displacements for each serial chain expressed as dual quaternions, and solve for up to five chains simultaneously to reach a number of positions along the hand trajectory. This is done using a hybrid global numerical solver that integrates a genetic algorithm and a Levenberg-Marquardt local optimizer. Although the number of candidate solutions in this problem is very high, the use of the genetic algorithm allows us to perform an exhaustive exploration of the solution space to obtain a set of solutions. We can then choose some of the solutions based on the specific task to perform. Note that these designs match the task exactly while generally having a finger design radically different from that of the human hand.


Author(s):  
Neda Hassanzadeh ◽  
Xiangwei He ◽  
Alba Perez-Gracia

The design of multi-fingered robotic hands can follow a kinematic synthesis approach, in which a trajectory or set of points and higher derivatives are defined for each fingertip. The output of the dimensional synthesis is a set of joint axes, effectively defining the basic kinematic structure of the hand. In the case of spatial motion, there seems to be a big gap between the results of the dimensional synthesis and a real and effective detailed design of the robotic hand, this being one of the reasons why synthesis is not regularly used in the design of robotic hands. This work aims to reduce the gap from kinematic synthesis to detailed, computer-aided design of robotic hands. In order to do so, the output of the dimensional synthesis is first used as the input of a link-based optimization process, aim to bring to reasonable values requirements such as link lengths, internal friction forces and obstacle avoidance, including self-intersection. The optimized results are automatically imported to a popular solid modeling software, creating reference geometry for parts, and joint axes and anchor points for the final hand assembly. At the same time, a database of hand parts is presented to the user to select and adapt in order to create a first realistic assembly of the robotic hand. The output of the process is a first detailed design of the robotic hand, which can be a good starting point for the designer to implement transmission and actuation in further stages.


Author(s):  
Connor M. McCann ◽  
Aaron M. Dollar

In this paper, we study the dimensional synthesis of a Stewart-Gough platform-inspired dexterous robotic hand, seeking to optimize the hand’s geometric design parameters to achieve the largest possible 6-degree-of-freedom workspace of a grasped object serving in the place of the “platform.” We present an analysis of the hand mechanism that considers both object stability from frictional contact forces as well as kinematic motion transmissibility, seeking a balance between these two properties. We examine the effect of variations in the kinematic and frictional parameters on both the workspace size of the hand as well as on the motion quality throughout the workspace across a range of grasped object sizes. We then present a spectrum of optimal designs that weight these two performance criteria differently. Most notably, the palm radius of the hand was found to have the greatest effect on the workspace size, with smaller palms exhibiting significantly larger workspaces. Overall, this work serves to inform the design process for dexterous robotic hands based on this common kinematic configuration, with the ultimate goal of increasing the dexterity of robotic manipulators to facilitate more versatile interactions with the environment.


2021 ◽  
Author(s):  
Md Omar Faruk Emon ◽  
Alex Russell ◽  
Gopal Nadkarni ◽  
Jae-Won Choi

Abstract Neuropathy is a nerve-damaging disease that causes those affected to lose feeling in their otherwise functional limbs. It can cause permanent numbing to the peripheral limb of a patient such as a hand or foot. In this report, we present a real-time visualization aid for grasp realization that can be used by patients experiencing numbness of the limb. This wearable electronic device was developed on an open-source microcontroller-based platform. This is a very simple and inexpensive solution. It is referred to as a NeuroGlove, and it provides patients with a visual light scale to allow them to understand the strength of the grasp they have on any object. A soft tactile sensor was additively manufactured by utilizing a multi-material direct-print system. The sensor consists of an ionic liquid-based pressure-sensitive membrane, stretchable electrodes, and insulation membranes. The printed flexible polymeric sensor was evaluated under varying forces. Next, the fabricated sensor was integrated with a microcontroller board where it was programmed to respond in a light scale according to the applied force on the sensor. Finally, the sensor-microcontroller system was installed on a glove to demonstrate a wearable visual aid for neuropathy patients. Additive manufacturing offers the ability for customization in a design, material, and geometry that could potentially lead to printing sensors on prosthetic or robotic hands.


2020 ◽  
Author(s):  
Nikoleta Lekaki ◽  
Marinos Costi ◽  
George Biskos ◽  
Anne Maisser

<p>Aerosol particles properties depend strongly on their particle size and they have significant effects on both, human health and environment. Nanometer sized particles possess special electrical, optical, and/or magnetic properties. This is one of the reasons which started the interest towards studying aerosol particles in the nanometer size range (Chen and Pui, 1995). The most efficient tool for determining the size of aerosol particle in the sub-micrometer and nanometer range is the differential mobility analyzer (DMA). This popular tool has two coaxial cylindrical electrodes between of them a potential difference is applied and forces the charged polydisperse aerosol to migrate from one electrode to another. Only those particles which have an electrical mobility in a narrow range, the will pass through the classifier (Stolzenburg, 1988).   Classifying aerosols according to their electrical mobility dates back to the first half of the 20<sup>th</sup> century and from that time plethora different DMAs have been build and their performances have been tested according to their transfer function and size resolution. One major limitation of classical DMAs is the time it takes to scan over the entire size range to get the size distribution of the aerosol. This is especially leading to the loss of information if the aerosol is changing its size and/or concentration rapidly. This happens for instance during new particle formation events, or also when the measurement takes place on fast moving platforms, such as cars, or airplanes.</p><p>The present work evaluates the performance of two different, newly developed DMA types, that aim towards overcoming this limitation. This is done by replacing the classic design of a single monodisperse outlet DMA to a multiple monodisperse outlet DMA. In our case the DMAs have three monodisperse outlets and are 3D-printed (namely, the 3MO-DMA) (Chen et al., 2007; Giamarelou et al., 2012; Barmpounis et al., 2016; Bezantakos et al., 2016). The 3MO-DMA is not only a fast response instrument able to sizing three different sizes ranges at the same time but also is a cost-effective and lightweight instrument suitable to get measurements not only ground based but also on Unmanned Aerial Vehicles or balloons.</p>


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